One of my projects
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For someone like me who rarely works with such complex models this is a very
interesting discussion. Out of my ignorance a couple of questions have popped into my aging synapses: -does the model include mutation and other adaptations by diseases? -are you going to study past massive epidemics to see what patterns are applicable (bio mimicry and incidence of natural immunity, cultural practices) -who will make the political choice to use the info/models when the time comes? Paul Paryski ************************************** See what's free at http://www.aol.com. -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070330/07b60e83/attachment.html |
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A few of you have asked questions about the the EpiSims-Grid project, so
I'll try to answer them here, in roughly inverse order that they were received: From: Paul Paryski: For someone like me who rarely works with such complex models this is a > very interesting discussion. Out of my ignorance a couple of questions have > popped into my aging synapses: > -does the model include mutation and other adaptations by diseases? > No, we have only simulated one pathogen at a time, to date, and it does not mutate. -are you going to study past massive epidemics to see what patterns are > applicable (bio mimicry and incidence of natural immunity, cultural > practices) > Yes, we have done this fairly extensively. Lots of data exists from the 1918 pandemic flu outbreak, for example. -who will make the political choice to use the info/models when the time > comes? > Good question. See my response to Laura Mac's questions bleow. >From Laura MacNamara: Being someone who studies people who use models, I'm curious about how you guys are relating to your user community. Who are the intended analysts (the ones that you hope know what you're doing)? At what point do you guys start engaging them? Do they treat your simulation as black box? Our last study was commissioned by a high-level consortium of Department-level representatives -- Dept. of State, Dept. of Treasury, Dept. of Homeland Security, Dept. of HHS, and the office of the White House. The purpose of the study was to help them identify relative measures of effectiveness regarding what intervention strategies would provide the most benefit in the event of a pandemic flu outbreak. Examples of intervention strategies that were modeled included 1. Self-isolation (staying home when symptomatic) 2. Social distancing (telecommuting, scheduled trips to the store with minimal contact to other shoppers, in general minimizing physical proximity to other people) during an outbreak 3. Closing down schools and non-critical workplaces 4. Treating critical infrastructure workers with anti-viral treatments (remember -- it was a pandemic being simulated, there were no vaccines) 5. etc. The intent was to help government officials develop a response plan in the event of an outbreak. I was quite impressed with the expertise with which the leader of the study, the White House representative, directed the study. He was one of the most knowledgeable and intelligent of any of the customers that I have aver worked with. The simulations used in the study were most definitely not treated as black boxes. Rather, the strengths and weaknesses of each of the three models were thoroughly explored. The consortium of users approached the leader of the MIDAS project and requested our participation on the project last summer, at which point we immediately engaged with them to develop an experimental design. >From Robert Holmes: Fair enough: big simulation answers some questions, small simulation answers others. So what are the specific questions that a big epidemiological simulation can answer? It can't be anything too predictive ("ohmigod, New York has just fallen to small pox. Which city is next?") because that depends (I'd guess) on something that is unsimulatable ("errr.... dunno. Kinda depends which flight the guy with small pox got onto"). What are the questions that can only be answered with a big model? EpiSims was by far the most detailed of the three models used. It is an individual-based ABM in which the second-to-second movements of every individual in the 8.6-million population city were modeled for 60 consecutive 24-hour days. Further, each individual was fairly completely characterized demographically -- race, inccome, marital status, number of children, etc. Also, family household structures are created by EpiSims, in which the same adults and children come back to the same household every day. This level of detail allowed us to run experiments on specific demographic subsets of the population that were not possible with the other models. For example, we ran a series of experiments for which social distancing was less effective among lower income people, because they could not afford to stay home -- they had to work. These runs were compared to runs where all working members of the population had the same compliance when social distancing measures were imposed. Another example of experiments that were conducted with EpiSims that could not be achieved with the other models: we ran several experiments in which the imuno-response of lower economic segments of the population was less effective in resisting the pandemic virus then for those more affluent members of the population. The reasoning being that poorer people have less access to health care. Remember, the intent of these studies was to establish a relative effectiveness ranking determination of various intervention strategies for future use establishing a response strategy in the event of a pandemic outbreak. The intent was *not* to model "ohmigod, New York has just fallen to small pox. Which city is next?" types of human behavior in response to an outbreak. I hope this addresses some of your questions. Thanks for your interest! --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070330/9514c858/attachment.html |
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Doug,
Did you not answer my question just because it seemed obvious or something? The other questions and your other answers all seemed very thoughtful, but didn't address mine. I'm thinking the use of the tool would include helping people in the learning process of finding what is actually working during the experience of an epidemic. Every pathogen and every public health initiative will have different growth dynamic characteristics, and sometimes very small differences will have large effects, especially because of relative lag times of divergence and response. I was commenting, I guess, on the difference between a universal general model of epidemic spread and response and the particular event process of an individual epidemic and the creative adaptation an effective response requires. Phil Henshaw ????.?? ? `?.???? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: pfh at synapse9.com explorations: www.synapse9.com <http://www.synapse9.com/> -----Original Message----- From: [hidden email] [mailto:[hidden email]] On Behalf Of Douglas Roberts Sent: Friday, March 30, 2007 5:45 PM To: The Friday Morning Applied Complexity Coffee Group Subject: Re: [FRIAM] One of my projects A few of you have asked questions about the the EpiSims-Grid project, so I'll try to answer them here, in roughly inverse order that they were received: From: Paul Paryski: For someone like me who rarely works with such complex models this is a very interesting discussion. Out of my ignorance a couple of questions have popped into my aging synapses: -does the model include mutation and other adaptations by diseases? No, we have only simulated one pathogen at a time, to date, and it does not mutate. -are you going to study past massive epidemics to see what patterns are applicable (bio mimicry and incidence of natural immunity, cultural practices) Yes, we have done this fairly extensively. Lots of data exists from the 1918 pandemic flu outbreak, for example. -who will make the political choice to use the info/models when the time comes? Good question. See my response to Laura Mac's questions bleow. >From Laura MacNamara: Being someone who studies people who use models, I'm curious about how you guys are relating to your user community. Who are the intended analysts (the ones that you hope know what you're doing)? At what point do you guys start engaging them? Do they treat your simulation as black box? Our last study was commissioned by a high-level consortium of Department-level representatives -- Dept. of State, Dept. of Treasury, Dept. of Homeland Security, Dept. of HHS, and the office of the White House. The purpose of the study was to help them identify relative measures of effectiveness regarding what intervention strategies would provide the most benefit in the event of a pandemic flu outbreak. Examples of intervention strategies that were modeled included 1. Self-isolation (staying home when symptomatic) 2. Social distancing (telecommuting, scheduled trips to the store with minimal contact to other shoppers, in general minimizing physical proximity to other people) during an outbreak 3. Closing down schools and non-critical workplaces 4. Treating critical infrastructure workers with anti-viral treatments (remember -- it was a pandemic being simulated, there were no vaccines) 5. etc. The intent was to help government officials develop a response plan in the event of an outbreak. I was quite impressed with the expertise with which the leader of the study, the White House representative, directed the study. He was one of the most knowledgeable and intelligent of any of the customers that I have aver worked with. The simulations used in the study were most definitely not treated as black boxes. Rather, the strengths and weaknesses of each of the three models were thoroughly explored. The consortium of users approached the leader of the MIDAS project and requested our participation on the project last summer, at which point we immediately engaged with them to develop an experimental design. >From Robert Holmes: Fair enough: big simulation answers some questions, small simulation answers others. So what are the specific questions that a big epidemiological simulation can answer? It can't be anything too predictive ("ohmigod, New York has just fallen to small pox. Which city is next?") because that depends (I'd guess) on something that is unsimulatable ("errr.... dunno. Kinda depends which flight the guy with small pox got onto"). What are the questions that can only be answered with a big model? EpiSims was by far the most detailed of the three models used. It is an individual-based ABM in which the second-to-second movements of every individual in the 8.6-million population city were modeled for 60 consecutive 24-hour days. Further, each individual was fairly completely characterized demographically -- race, inccome, marital status, number of children, etc. Also, family household structures are created by EpiSims, in which the same adults and children come back to the same household every day. This level of detail allowed us to run experiments on specific demographic subsets of the population that were not possible with the other models. For example, we ran a series of experiments for which social distancing was less effective among lower income people, because they could not afford to stay home -- they had to work. These runs were compared to runs where all working members of the population had the same compliance when social distancing measures were imposed. Another example of experiments that were conducted with EpiSims that could not be achieved with the other models: we ran several experiments in which the imuno-response of lower economic segments of the population was less effective in resisting the pandemic virus then for those more affluent members of the population. The reasoning being that poorer people have less access to health care. Remember, the intent of these studies was to establish a relative effectiveness ranking determination of various intervention strategies for future use establishing a response strategy in the event of a pandemic outbreak. The intent was *not* to model "ohmigod, New York has just fallen to small pox. Which city is next?" types of human behavior in response to an outbreak. I hope this addresses some of your questions. Thanks for your interest! --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070331/bbda929e/attachment.html |
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Phil,
I did read your question, repeated below: Cool, do you include any comparative natural system component? Perhaps working with better ways to identify system structures in natural systems and early signs of when they are inventing new ones would be helpful in developing tests for models that approximate the complexity of nature. However, I found it to be sufficiently ambiguous that I had absolutely no idea what was being asked, and thus found myself at a complete loss for a response. -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell On 3/31/07, Phil Henshaw <sy at synapse9.com> wrote: > > Doug, > Did you not answer my question just because it seemed obvious or > something? The other questions and your other answers all seemed very > thoughtful, but didn't address mine. I'm thinking the use of the tool > would include helping people in the learning process of finding what is > actually working during the experience of an epidemic. Every pathogen and > every public health initiative will have different growth dynamic > characteristics, and sometimes very small differences will have large > effects, especially because of relative lag times of divergence and > response. I was commenting, I guess, on the difference between a > universal general model of epidemic spread and response and the particular > event process of an individual epidemic and the creative adaptation an > effective response requires. > > > > Phil Henshaw ????.?? ? `?.???? > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > 680 Ft. Washington Ave > NY NY 10040 > tel: 212-795-4844 > e-mail: pfh at synapse9.com > explorations: www.synapse9.com > > -----Original Message----- > *From:* friam-bounces at redfish.com [mailto:friam-bounces at redfish.com] *On > Behalf Of *Douglas Roberts > *Sent:* Friday, March 30, 2007 5:45 PM > *To:* The Friday Morning Applied Complexity Coffee Group > *Subject:* Re: [FRIAM] One of my projects > > A few of you have asked questions about the the EpiSims-Grid project, so > I'll try to answer them here, in roughly inverse order that they were > received: > > > > From: Paul Paryski: > > For someone like me who rarely works with such complex models this is a > > very interesting discussion. Out of my ignorance a couple of questions have > > popped into my aging synapses: > > -does the model include mutation and other adaptations by diseases? > > > > No, we have only simulated one pathogen at a time, to date, and it does > not mutate. > > -are you going to study past massive epidemics to see what patterns are > > applicable (bio mimicry and incidence of natural immunity, cultural > > practices) > > > > Yes, we have done this fairly extensively. Lots of data exists from the > 1918 pandemic flu outbreak, for example. > > -who will make the political choice to use the info/models when the time > > comes? > > > > Good question. See my response to Laura Mac's questions bleow. > > From Laura MacNamara: > > Being someone who studies people who use models, I'm curious about how you > guys are relating to your user community. Who are the intended analysts > (the ones that you hope know what you're doing)? At what point do you guys > start engaging them? Do they treat your simulation as black box? > > > Our last study was commissioned by a high-level consortium of > Department-level representatives -- Dept. of State, Dept. of Treasury, Dept. > of Homeland Security, Dept. of HHS, and the office of the White House. The > purpose of the study was to help them identify relative measures of > effectiveness regarding what intervention strategies would provide the most > benefit in the event of a pandemic flu outbreak. Examples of intervention > strategies that were modeled included > > 1. Self-isolation (staying home when symptomatic) > 2. Social distancing (telecommuting, scheduled trips to the store > with minimal contact to other shoppers, in general minimizing physical > proximity to other people) during an outbreak > 3. Closing down schools and non-critical workplaces > 4. Treating critical infrastructure workers with anti-viral > treatments (remember -- it was a pandemic being simulated, there were no > vaccines) > 5. etc. > > The intent was to help government officials develop a response plan in the > event of an outbreak. I was quite impressed with the expertise with which > the leader of the study, the White House representative, directed the > study. He was one of the most knowledgeable and intelligent of any of the > customers that I have aver worked with. The simulations used in the study > were most definitely not treated as black boxes. Rather, the strengths and > weaknesses of each of the three models were thoroughly explored. > > The consortium of users approached the leader of the MIDAS project and > requested our participation on the project last summer, at which point we > immediately engaged with them to develop an experimental design. > > From Robert Holmes: > > Fair enough: big simulation answers some questions, small simulation > answers others. So what are the specific questions that a big > epidemiological simulation can answer? It can't be anything too predictive > ("ohmigod, New York has just fallen to small pox. Which city is next?") > because that depends (I'd guess) on something that is unsimulatable > ("errr.... dunno. Kinda depends which flight the guy with small pox got > onto"). What are the questions that can only be answered with a big model? > > EpiSims was by far the most detailed of the three models used. It is an > individual-based ABM in which the second-to-second movements of every > individual in the 8.6-million population city were modeled for 60 > consecutive 24-hour days. Further, each individual was fairly completely > characterized demographically -- race, inccome, marital status, number of > children, etc. Also, family household structures are created by EpiSims, in > which the same adults and children come back to the same household every > day. > > This level of detail allowed us to run experiments on specific demographic > subsets of the population that were not possible with the other models. For > example, we ran a series of experiments for which social distancing was less > effective among lower income people, because they could not afford to stay > home -- they had to work. These runs were compared to runs where all > working members of the population had the same compliance when social > distancing measures were imposed. > > Another example of experiments that were conducted with EpiSims that could > not be achieved with the other models: we ran several experiments in which > the imuno-response of lower economic segments of the population was less > effective in resisting the pandemic virus then for those more affluent > members of the population. The reasoning being that poorer people have less > access to health care. > > Remember, the intent of these studies was to establish a relative > effectiveness ranking determination of various intervention strategies for > future use establishing a response strategy in the event of a pandemic > outbreak. The intent was *not* to model "ohmigod, New York has just > fallen to small pox. Which city is next?" types of human behavior in > response to an outbreak. > > I hope this addresses some of your questions. Thanks for your interest! > > --Doug > > > > -- > Doug Roberts, RTI International > droberts at rti.org > doug at parrot-farm.net > 505-455-7333 - Office > 505-670-8195 - Cell > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070331/622d3a3e/attachment.html |
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In reply to this post by Douglas Roberts-2
Congratulations Douglas
1) Do you include different levels of virulence in your simulation? 2) Do you consider vectors in the spread of diseases ? 3) Will you extend your work to study other pathosystems (I mean in plants or even arthropoda)? Regards Alfredo --------------------------- Alfredo Covaleda V?lez Ingeniero Agr?nomo - Programador Tel?fono: 3112137829 Bogot? D.C. - Colombia --------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070403/b9a572c0/attachment.html |
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Hi, Alfredo.
In the past, we have modeled a variety of influenza strains, some more virulent than others. We have conducted simulations of infections of influenza A & B, avian influenza, as well as smallpox, anthrax, pneumonic plague and bubonic plague in a series of previous studies. The vectors of disease spread emerge from the person-person interactions as EpiSims simulates the second-to-second movements and activities of all people in the region of interest. These interactions occur in the work place, at home, while shopping, during recreational activities, while commuting, etc. The vectors of disease spread are of course studied for insight into potential intervention strategies. EpiSims can be used to model the spread of any infectious agent whose human health characteristics can be captured by a Markov chain state representation. Regards, --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office On 4/2/07, Alfredo <agbioinfo at gmx.net> wrote: > > Congratulations Douglas > > 1) Do you include different levels of virulence in your simulation? > > > 2) Do you consider vectors in the spread of diseases ? > > > 3) Will you extend your work to study other pathosystems (I mean in plants > or even arthropoda)? > > > Regards > > Alfredo > > --------------------------- > Alfredo Covaleda V?lez > Ingeniero Agr?nomo - Programador > Tel?fono: 3112137829 > Bogot? D.C. - Colombia > --------------------------- > > > > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > 505-670-8195 - Cell -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070403/3c2140d3/attachment.html |
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In reply to this post by Douglas Roberts-2
Doug,
I wonder how EpiSIMS results would compare to introducing a viral actor into "The SIMS" ore "Second Life"? Would there be some difference in emergent behavior of real people running their avatars from agents, however realistically programmed, running their code? -- Ray Parks rcparks at sandia.gov IDART Project Lead Voice:505-844-4024 IORTA Department Mobile:505-238-9359 http://www.sandia.gov/scada Fax:505-844-9641 http://www.sandia.gov/idart Pager:800-690-5288 |
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Hi, Ray.
One will seldom, if ever get identical behavior from two different codes, even if the inputs are identical. The emergent behavior that could be observed from EpiSims, The SIMS, and Second Life, assuming the latter two could emulate responses to the introduction of a viral pathogen, will vary based directly on the differences of granularity with with the agents are implemented in the simulations. --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell On 4/4/07, Raymond Parks <rcparks at sandia.gov> wrote: > > Doug, > > I wonder how EpiSIMS results would compare to introducing a viral > actor into "The SIMS" ore "Second Life"? Would there be some difference > in emergent behavior of real people running their avatars from agents, > however realistically programmed, running their code? > > -- > Ray Parks rcparks at sandia.gov > IDART Project Lead Voice:505-844-4024 > IORTA Department Mobile:505-238-9359 > http://www.sandia.gov/scada Fax:505-844-9641 > http://www.sandia.gov/idart Pager:800-690-5288 > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070404/998ad4c0/attachment.html |
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Doug,
You wrote: > One will seldom, if ever get identical behavior from two different > codes, even if the inputs are identical. > > The emergent behavior that could be observed from EpiSims, The SIMS, and > Second Life, assuming the latter two could emulate responses to the > introduction of a viral pathogen, will vary based directly on the > differences of granularity with with the agents are implemented in the > simulations. Given that the "agents" in The Sims and Second Life are avatars for real people, one could argue that their code is more realistic than agent code. Their granularity is basically as small as one can get - some MMORPGs allow for more than one character per player but they are still one character per character. One problem I can see would be that MMORPGs in general suffer from the lack of full participation - EpiSims models every second of human behaviour for a large population, but MMORPG players are not playing their avatars all of the time. I wonder if some combination would play to the strengths of both systems. Could one use something like EpiSims running at wall-clock speed as the background for avatars played by real people? Then the simulated people agent code could self-modify on the fly to model the behaviour of the real people. I'm starting to sound like the explanation of the fake Rock Ridge in "Blazing Saddles". -- Ray Parks rcparks at sandia.gov IDART Project Lead Voice:505-844-4024 IORTA Department Mobile:505-238-9359 http://www.sandia.gov/scada Fax:505-844-9641 http://www.sandia.gov/idart Pager:800-690-5288 |
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Ray,
Please explain how the "avatars" will know when they have been infected by a virus, and how they will respond to that. In fact, please explain how the "avatars" know when go to work, when and where to go shopping, know when an epidemic has been announced; how they will respond to a decreed intervention strategy of keeping the kids home from school? What will be the "avatar" level of compliance to the declared regime of intervention strategy? How many will accept anti-viral treatment? How many will wear masks to work? How many will comply to government requests to self-isolate when they become symptomatic? How will an "avatar" determine when it has become symptomatic? With what level of resolution will these "avatars" behave in the simulation? --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell On 4/4/07, Raymond Parks <rcparks at sandia.gov> wrote: > > Doug, > > You wrote: > > One will seldom, if ever get identical behavior from two different > > codes, even if the inputs are identical. > > > > The emergent behavior that could be observed from EpiSims, The SIMS, and > > Second Life, assuming the latter two could emulate responses to the > > introduction of a viral pathogen, will vary based directly on the > > differences of granularity with with the agents are implemented in the > > simulations. > > Given that the "agents" in The Sims and Second Life are avatars for > real people, one could argue that their code is more realistic than > agent code. Their granularity is basically as small as one can get - > some MMORPGs allow for more than one character per player but they are > still one character per character. One problem I can see would be that > MMORPGs in general suffer from the lack of full participation - EpiSims > models every second of human behaviour for a large population, but > MMORPG players are not playing their avatars all of the time. > > I wonder if some combination would play to the strengths of both > systems. Could one use something like EpiSims running at wall-clock > speed as the background for avatars played by real people? Then the > simulated people agent code could self-modify on the fly to model the > behaviour of the real people. I'm starting to sound like the > explanation of the fake Rock Ridge in "Blazing Saddles". > > -- > Ray Parks rcparks at sandia.gov > IDART Project Lead Voice:505-844-4024 > IORTA Department Mobile:505-238-9359 > http://www.sandia.gov/scada Fax:505-844-9641 > http://www.sandia.gov/idart Pager:800-690-5288 > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070404/b7687050/attachment.html |
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In reply to this post by Parks, Raymond
I've always disliked the term ABM because the notion of intelligent or
semi-intelligent actors is a distraction. Really ABM and rule based modeling are the same thing. Agents models can be of car engines, etc. Defined conservatively, say to understand human behavioral patterns in virtual worlds as opposed to human behaviors in general, it does seem that human vs. computer agents could be useful to mix and match for modeling. Say, to refine models of the range of individual behavioral patterns for the sake of make predictions of groups of people in yet to be designed virtual worlds.. |
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Ah, yes... very significant observation. And then how do you represent the
systems of nature that are out of control and making up altogether new rules??? And how do you tell which is which? If you're a real pest for detailed observation you find that our rule making is always an idealization of a conceptual level of organization in nature, not the real behavior of nature. It's tough, but we're stumbling over the error of representing our ways of predicting events as the mechanism by which nature performs events. Its-a just not-a da case! On 4/4/07, Marcus G. Daniels <marcus at snoutfarm.com> wrote: > > I've always disliked the term ABM because the notion of intelligent or > semi-intelligent actors is a distraction. Really ABM and rule based > modeling are the same thing. Agents models can be of car engines, etc. > > Defined conservatively, say to understand human behavioral patterns in > virtual worlds as opposed to human behaviors in general, it does seem > that human vs. computer agents could be useful to mix and match for > modeling. Say, to refine models of the range of individual behavioral > patterns for the sake of make predictions of groups of people in yet to > be designed virtual worlds.. > > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > > An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070404/32eda862/attachment.html |
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Phil Henshaw wrote:
> how do you represent the systems of nature that are out of control and > making up altogether new rules??? At some point that kind effort is less of an empirical science and more of a mathematical investigation into worlds as they could be. That's not to say it is bad, it's just a different goal. One way to proceed with that kind of investigation is with genetic programming. Create an imaginary world that has certain forces acting on the things in it, and then evolve computer programs that can survive in that imaginary world. After the agents survive very well, take apart those computer programs to try figure out how they work, or study how different computer programs interact in that world and possibly even change it. Classic example: http://www.archive.org/details/sims_evolved_virtual_creatures_1994 With an avatar/gaming world, it's not hard to imagine automated agents learning how to fight or cooperate with human players. Then one could probe those agents to watch how they make decisions. To be more systematic and learn about learning one could have timestamps on each node/branch to compare the recent innovations from enduring logic. |
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NOTE: Apologies if this is duplicated. Got a note back that I used the wrong
email addy on my last attempt, but it's Gmail, so it shows my response in the chain anyway... For an instance that may be somewhat akin to what's being discussed here, I'd refer back to an even from two years ago in the MMORPG World of Warcraft. A "plague" that was designed by the game programmers and intended to be restricted to a particular server actually made its way onto other servers. The plague spread rapidly, producing a fascinating -- to me, anyway -- array of reactions. More on the issue is here: http://www.securityfocus.com/news/11330 . In response to the question "how would the avatars know when they were infected?", this was actually part of the game: health of the character decreased incrementally. The plague could be spread, treated but not cured, cured, etc. What I found most compelling was that the WoW community responded in many of the same ways as you'd think people would in the face of a real disaster. Whole neighborhoods banned entrance from unknown players, some altruistic people went around giving out healing/resurrection spells (things that have to be bought with money that is earned through time playing the game, so not entirely without value), while still others thought it amusing to spread the virus as far as possible. There were even debates in various fora about retaining or eliminating the potential for such an outbreak; that it got out of the hands of the designers enhanced the realism to some, made the gameplay worse to others. In the wake of the virus in WoW, I sent the people at Blizzard Entertainment inquiries about getting anonymized data on various things they track, but got a polite "You must be joking, right?" While we often can't run experiments on humans, with the growth of involvement in games like WoW, Second Life, Eve, etc, would it be impossible to consider experimenting in these realms? The big mean bad guys in MMORPGS are rather like agents, so there's already some precedent for mixing the two. There's a growing study of gameworld macroeconomics, the value of time people expend in increasing their online holdings (to the point of "gold farming" being a big job for kids in urban China and South Korea), and so on. -Ian On 4/4/07, Marcus G. Daniels <marcus at snoutfarm.com> wrote: > > Phil Henshaw wrote: > > how do you represent the systems of nature that are out of control and > > making up altogether new rules??? > At some point that kind effort is less of an empirical science and more > of a mathematical investigation into worlds as they could be. That's > not to say it is bad, it's just a different goal. > > One way to proceed with that kind of investigation is with genetic > programming. Create an imaginary world that has certain forces acting > on the things in it, and then evolve computer programs that can survive > in that imaginary world. After the agents survive very well, take > apart those computer programs to try figure out how they work, or study > how different computer programs interact in that world and possibly even > change it. Classic example: > > http://www.archive.org/details/sims_evolved_virtual_creatures_1994 > > With an avatar/gaming world, it's not hard to imagine automated agents > learning how to fight or cooperate with human players. Then one could > probe those agents to watch how they make decisions. To be more > systematic and learn about learning one could have timestamps on each > node/branch to compare the recent innovations from enduring logic. > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > -- ___________________________________ Ian P. Cook m: 703.405.0279 h: 703.578.0798 jabber: ianpcook at gmail.com Y!/MSN: ian_palmer_cook AIM: ianpalmercook ___________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070405/37c3b1ff/attachment.html |
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In reply to this post by Douglas Roberts-2
Doug,
You wrote: > Please explain how the "avatars" will know when they have been infected > by a virus, and how they will respond to that. The avatar may or may not know, depending upon the implementation. The real question is whether the player of the avatar knows. This is something that would have to be crafted into the simulation. Let me write this up in a logical way. ------------------------------------------------------------------ if the AVATAR is exposed to the disease then if the exposure is sufficient then //(ACPLA > X, transferred virii > 50% infection probability or whatever) set the infected flag in the AVATAR set incubation time start the incubation timer counting to incubation time endif endif // Player continues to play AVATAR normally // Ignore infectious incubation periods for now // Increment incubation timer each second as part of simulation cycle if the incubation timer is equal to incubation time then set the active flag in the AVATAR set the disease time // This could be to death, to recovery, or other outcome start the disease timer counting to disease time endif // Then, for each simulation cycle look up symptoms using disease timer inform player of AVATAR symptoms // "You feel tired and your muscles ache." ------------------------------------------------------------------ The player of the AVATAR should respond in an appropriate way, probably based on their real-life experience. Some will ignore the symptoms until their AVATAR starts functioning poorly (doesn't move as fast, doesn't notice the bus about to run them down, or whatever). Some will promptly go to a doctor. Some may seek advice from other AVATARs representing trusted counselors (parents, grandparents, etc). All of these will have different effects on the spread of an epidemic and are not something you would think to model. That's the point of using real humans - they do the darndest things that you'd never expect. If you don't take those strange actions into account, your sim could give you an answer that has nothing to do with the real world. > In fact, please explain how the "avatars" know when go to work, How do you know when to go to work? Somebody told you. If you have real humans playing an AVATAR in your simulation, they will have to be briefed on the role they must play. "You're a computer scientist who has to arrive at the lab every morning at 0830, gets a half hour for lunch somewhere between 1100 and 1300, and may go home at 1700." > when and where to go shopping, "You open the refrigerator to see what you can make for dinner and there's nothing there." > know when an epidemic has been announced; "You hear the funny honking of the emergency broadcast network on your car radio. An announcer says there is an epidemic raging in your town." > how they will respond to a decreed intervention strategy of keeping the kids home > from school? "The emergency announcer says you must keep your kids home from school." In the type of MMORPG we're talking about, its likely that the kids are not played by real people but by your agents. The interaction between the agents and the parent will drive the actions of the parent AVATAR's player. If the simulation informs the parent that their kids are driving them crazy, the parent may decide not to keep them home from school. If the initial briefing informed the role-player that they are short on money, they may decide not to stay home with the kids or to let the kids roam freely while the role-player's AVATAR goes to work. > What will be the "avatar" level of compliance to the > declared regime of intervention strategy? How many will accept > anti-viral treatment? How many will wear masks to work? How many will > comply to government requests to self-isolate when they become > symptomatic? These are all decisions that the player will make in playing the AVATAR. That's the point of using real people to help your simulation be real. We would have to design mechanisms to provide the correct feedback to the player. You already mentioned that your sim has provision for poor folks who can't afford not to work. The player would just be informed of the same information - "Your rent is due next Friday and you don't have enough money." - to which the player can either decide to go to work or to follow orders and stay home. To get the reasonable results from the players, the sim needs to provide feedback. This doesn't have to be realistic as long as the result is the same. MMORPGs have mechanisms to do this type of thing without requiring every actor be role-played. In Star Wars Galaxies, certain professions can "mine" resources - these aren't just minerals. Rather than play out the various processes required for mining minerals or growing plants, the player has to spend time in a certain spot in the game world clicking on a point or something. Each click increments the resource count by a miniscule amount. The intent is that the AVATAR spends time in a particular location doing some activity to collect resources. It's the spending of time and lack of movement/participation that is the behaviour to be modeled, not the actions necessary to collect the resources. > How will an "avatar" determine when it has become > symptomatic? All we can do is tell the player that their AVATAR has certain symptoms. Depending upon whether we want to make this easy or not, we can use the same words as the government request or use different words that require the player to interpret them - just as a person would have to interpret their symptoms in a real epidemic. Some people think they can't move they ache so badly and others think the muscle ache is a minor annoyance. In a straight simulation, you model this with some sort of normal distribution of how many will comply. I'm proposing that we model compliance with real people and then turn around and use that number in the agents. > With what level of resolution will these "avatars" behave in the simulation? That's the real difficulty. In effect, we would be federating two simulations in the same structure, and getting timing to match between two federated simulations is always a problem. We have the most control over the agent simulation - we can run it faster or slower to match the turn speed we give to the human-played AVATARs. Fortunately, it isn't necessary for the human players to enter their actions every second - they can enter courses of action (go out door - get in car - drive to work - walk into office - ....) which can then be played out in time to match the agent simulation. If the agent sim runs faster than real-time, we can see if that still matches the COA level of the human players. If the agent sim is too fast, we can throttle it back (or add more agents). If the agent sim runs too slow, we can coarsen the time for each turn for the human - instead of asking the human player to choose what their AVATAR does for the next five minutes, we ask them to choose for the next ten minutes. I'm detecting a certain stridency in your replies. I hope I'm wrong and you're not upset at my suggestion. That's all this is - a suggestion. It may not be feasible and I certainly have no stake in this idea. It was just something I threw out based on my experience as a role-playing gamer and my limited knowledge of MMORPGs. -- Ray Parks rcparks at sandia.gov IDART Project Lead Voice:505-844-4024 IORTA Department Mobile:505-238-9359 http://www.sandia.gov/scada Fax:505-844-9641 http://www.sandia.gov/idart Pager:800-690-5288 |
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In reply to this post by Marcus G. Daniels
I mainly just learn to identify islanded causal chains, and by long
experience find that when they result in things I can then replace in my mind with rules, I'm forced to say that the local system made them up. Phil Henshaw ????.?? ? `?.???? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: pfh at synapse9.com explorations: www.synapse9.com > -----Original Message----- > From: friam-bounces at redfish.com > [mailto:friam-bounces at redfish.com] On Behalf Of Marcus G. Daniels > Sent: Wednesday, April 04, 2007 11:38 PM > To: The Friday Morning Applied Complexity Coffee Group > Subject: Re: [FRIAM] One of my projects > > > Phil Henshaw wrote: > > how do you represent the systems of nature that are out of > control and > > making up altogether new rules??? > At some point that kind effort is less of an empirical > science and more > of a mathematical investigation into worlds as they could be. That's > not to say it is bad, it's just a different goal. > > One way to proceed with that kind of investigation is with genetic > programming. Create an imaginary world that has certain > forces acting > on the things in it, and then evolve computer programs that > can survive > in that imaginary world. After the agents survive very well, take > apart those computer programs to try figure out how they > work, or study > how different computer programs interact in that world and > possibly even > change it. Classic example: > With an avatar/gaming world, it's not hard to imagine automated agents learning how to fight or cooperate with human players. Then one could probe those agents to watch how they make decisions. To be more systematic and learn about learning one could have timestamps on each node/branch to compare the recent innovations from enduring logic. ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org |
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In reply to this post by Parks, Raymond
Hey, Ray.
No, I'm not upset. I believe the original question was (paraphrasing) "Wouldn't an avatar-based system produce more accurate epidemiological simulation results than other agent based models, such as EpiSims?" The point of the questions that I blasted back at you was to illustrate that the resolution of the disease representation, and the characterization of disease progression in the individuals in a population is as important, if not more so that the ability to simulate any human decision-making behavior (which presumably would be your motivation for suggesting an avatar-based approach). A population is comprised of old, young, immuno-suppressed, and "normal" healthy individuals. Any particular disease will propagate at different rates, with different individual responses when it is attacking the population. An avatar-based simulation would not be any better representing at that than any agent-based simulation would be. Equally important to fidelity in representation of the disease impact on individual members of the population, and on the population as a whole is the fidelity of representation of the population mobility patterns in the system being modeled. Disease such as influenza is spread by contact, and if you don't have accurate representations of the population mobility patterns, your results will be meaningless. An avatar-based simulation would probably be *much* worse at modeling population contact patterns than a simulation such as EpiSims, Epicast, or a number of other population mobility-based simulations, because the population mobility patterns in those simulations are at least validated. The whole precept of avatar-based simulations is that with such, you supposedly get better representations of human decision processes. I don't believe that. And in particular, I don't believe it when it comes to modeling large complex urban areas in which a biological agent is discovered to have been introduced into the system. --Doug -- Doug Roberts, RTI International droberts at rti.org doug at parrot-farm.net 505-455-7333 - Office 505-670-8195 - Cell On 4/5/07, Raymond Parks <rcparks at sandia.gov> wrote: > > Doug, > > You wrote: > > Please explain how the "avatars" will know when they have been infected > > by a virus, and how they will respond to that. > > The avatar may or may not know, depending upon the implementation. > The real question is whether the player of the avatar knows. This is > something that would have to be crafted into the simulation. Let me > write this up in a logical way. > > ------------------------------------------------------------------ > if the AVATAR is exposed to the disease then > if the exposure is sufficient then > //(ACPLA > X, transferred virii > 50% infection probability or whatever) > set the infected flag in the AVATAR > set incubation time > start the incubation timer counting to incubation time > endif > endif > > // Player continues to play AVATAR normally > // Ignore infectious incubation periods for now > // Increment incubation timer each second as part of simulation cycle > > if the incubation timer is equal to incubation time then > set the active flag in the AVATAR > set the disease time > // This could be to death, to recovery, or other outcome > start the disease timer counting to disease time > endif > > // Then, for each simulation cycle > > look up symptoms using disease timer > inform player of AVATAR symptoms > // "You feel tired and your muscles ache." > ------------------------------------------------------------------ > > The player of the AVATAR should respond in an appropriate way, > probably based on their real-life experience. Some will ignore the > symptoms until their AVATAR starts functioning poorly (doesn't move as > fast, doesn't notice the bus about to run them down, or whatever). Some > will promptly go to a doctor. Some may seek advice from other AVATARs > representing trusted counselors (parents, grandparents, etc). All of > these will have different effects on the spread of an epidemic and are > not something you would think to model. That's the point of using real > humans - they do the darndest things that you'd never expect. If you > don't take those strange actions into account, your sim could give you > an answer that has nothing to do with the real world. > > > In fact, please explain how the "avatars" know when go to work, > > How do you know when to go to work? Somebody told you. If you have > real humans playing an AVATAR in your simulation, they will have to be > briefed on the role they must play. > > "You're a computer scientist who has to arrive at the lab every > morning at 0830, gets a half hour for lunch somewhere between 1100 and > 1300, and may go home at 1700." > > > when and where to go shopping, > > "You open the refrigerator to see what you can make for dinner and > there's nothing there." > > > know when an epidemic has been announced; > > "You hear the funny honking of the emergency broadcast network on > your car radio. An announcer says there is an epidemic raging in your > town." > > > how they will respond to a decreed intervention strategy of keeping the > kids home > > from school? > > "The emergency announcer says you must keep your kids home from > school." > > In the type of MMORPG we're talking about, its likely that the kids > are not played by real people but by your agents. The interaction > between the agents and the parent will drive the actions of the parent > AVATAR's player. If the simulation informs the parent that their kids > are driving them crazy, the parent may decide not to keep them home from > school. If the initial briefing informed the role-player that they are > short on money, they may decide not to stay home with the kids or to let > the kids roam freely while the role-player's AVATAR goes to work. > > > What will be the "avatar" level of compliance to the > > declared regime of intervention strategy? How many will accept > > anti-viral treatment? How many will wear masks to work? How many will > > comply to government requests to self-isolate when they become > > symptomatic? > > These are all decisions that the player will make in playing the > AVATAR. That's the point of using real people to help your simulation > be real. We would have to design mechanisms to provide the correct > feedback to the player. You already mentioned that your sim has > provision for poor folks who can't afford not to work. The player would > just be informed of the same information - "Your rent is due next Friday > and you don't have enough money." - to which the player can either > decide to go to work or to follow orders and stay home. To get the > reasonable results from the players, the sim needs to provide feedback. > This doesn't have to be realistic as long as the result is the same. > > MMORPGs have mechanisms to do this type of thing without requiring > every actor be role-played. In Star Wars Galaxies, certain professions > can "mine" resources - these aren't just minerals. Rather than play out > the various processes required for mining minerals or growing plants, > the player has to spend time in a certain spot in the game world > clicking on a point or something. Each click increments the resource > count by a miniscule amount. The intent is that the AVATAR spends time > in a particular location doing some activity to collect resources. It's > the spending of time and lack of movement/participation that is the > behaviour to be modeled, not the actions necessary to collect the > resources. > > > How will an "avatar" determine when it has become > > symptomatic? > > All we can do is tell the player that their AVATAR has certain > symptoms. Depending upon whether we want to make this easy or not, we > can use the same words as the government request or use different words > that require the player to interpret them - just as a person would have > to interpret their symptoms in a real epidemic. Some people think they > can't move they ache so badly and others think the muscle ache is a > minor annoyance. In a straight simulation, you model this with some > sort of normal distribution of how many will comply. I'm proposing that > we model compliance with real people and then turn around and use that > number in the agents. > > > With what level of resolution will these "avatars" behave in the > simulation? > > That's the real difficulty. In effect, we would be federating two > simulations in the same structure, and getting timing to match between > two federated simulations is always a problem. We have the most control > over the agent simulation - we can run it faster or slower to match the > turn speed we give to the human-played AVATARs. Fortunately, it isn't > necessary for the human players to enter their actions every second - > they can enter courses of action (go out door - get in car - drive to > work - walk into office - ....) which can then be played out in time to > match the agent simulation. If the agent sim runs faster than > real-time, we can see if that still matches the COA level of the human > players. If the agent sim is too fast, we can throttle it back (or add > more agents). If the agent sim runs too slow, we can coarsen the time > for each turn for the human - instead of asking the human player to > choose what their AVATAR does for the next five minutes, we ask them to > choose for the next ten minutes. > > I'm detecting a certain stridency in your replies. I hope I'm wrong > and you're not upset at my suggestion. That's all this is - a > suggestion. It may not be feasible and I certainly have no stake in > this idea. It was just something I threw out based on my experience as > a role-playing gamer and my limited knowledge of MMORPGs. > > -- > Ray Parks rcparks at sandia.gov > IDART Project Lead Voice:505-844-4024 > IORTA Department Mobile:505-238-9359 > http://www.sandia.gov/scada Fax:505-844-9641 > http://www.sandia.gov/idart Pager:800-690-5288 > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org > An HTML attachment was scrubbed... URL: http://redfish.com/pipermail/friam_redfish.com/attachments/20070405/bfba911d/attachment.html |
human/computer simulated environments
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In reply to this post by Parks, Raymond
For any virtual sociologists out there.. second Life is being open sourced!
http://blogs.zdnet.com/social/?p=142 |
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