Re: [FRIAM] Agent-Based Modelling
I am not sure if agent-based modelling offers better insight than the knowledge of history combined with common sense, but it is probably much better than Game Theory and pure mathematical analysis. One problem is the myriad ways in which actors in societies can interact with each other: if seventy agents were lining up to enter a gate, there are 70! different ways how this could be arranged ( which equals roughly 10^100, see http://en.wikipedia.org/wiki/Googol ) Another factor that makes modeling of real societies difficult is the intractable individual behavior (which depends on prejudices, preferences, personal experiences, etc.). Jared Diamond writes in his No.1 bestseller Collapse in chapter 9 Opposite Paths to Success/Other Successes that even ...people with long-term stakes don't always act wisely. Often they still prefer short-term goals, and often again they do things that are foolish in both the short term and the long term. That's what makes biography and history infinitely more complicated and less predictable than the courses of chemical reactions... -J. From: Robert Cordingley Subject: Re: [FRIAM] Agent-Based Modelling of a Blowback - How Terrorists are made [...] The question has to be answered: does the process work in this domain? Do the ethnographic studies, the incorporation of the best political advisors, etc., perhaps with the use of all the computing power you can dream of, along with the latest and sharpest computing tools produce a system that has measurable performance against the real world. What is the probability that when X is tested, Y will occur? When does chaos takeover? Is it meaningful in the time it takes to implement policy? Having performance based results are key to success and probably not readily shared. 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
Re: [FRIAM] Social networking sites
Good idea, but a lot of others had it, too. There is already a large number of social networking sites with web interfaces that are building and organizing themselves. For example, to name a few, http://groups.yahoo.com/ http://groups.msn.com/ http://www.myspace.com/ http://www.friendster.com/ http://www.linkedin.com/ http://www.netrelate.com/ http://cluster.tribe.net/ More are listed at http://en.wikipedia.org/wiki/Social_networking_sites -J. From: Nicholas Thompson Sent: Wednesday, August 09, 2006 4:31 AM Subject: [FRIAM] The first day of the rest of nick's life [...] One project that seems particularly worthy, whose working name is the Purple People Project, seeks to provide a web dating service for people or web chess club who want to talk to, argue with, share views with, , people who disagree with them on major issues of the day. I imagine a web interface which would help people find one another and then structure thier discussions to keep people away from unproductive discourse or perhaps to guide them toward productive discourse. I think to get it rolling we would need web people, philosophical people, political people. What I would love to think of is some way in which the site could build itself [...] Has anybody out there had similar thoughts??? 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
[FRIAM] **today** Lecture: Wed Aug 9 2p, Douglas Samuelson: Attention Allocation in Organizational Decision-Making
** today / non-standard time of 2p ** TITLE: Attention Allocation in Organizational Decision-Making SPEAKER: Douglas A. Samuelson AFFILIATION: Homeland Security Institute LOCATION: 624 Agua Fria Conference Room TIME: Wed August 9, ** 2:00p ** (non-standard time) ABSTRACT: Consider how to improve organizational decision-making by streamlining the process of seeking and allocating the attention of top decision-makers. These decision-makers try to optimize the value they receive by allocating their attention, taking uncertainty into account. In fact, optimizing the benefits of attention results, for the organization's original problem, in the well-known satisficing behavior described by Herbert Simon. In practice, the behavior is often similar to the greedy heuristic for the knapsack problem: a few of the largest topics and many small topics get addressed, while most middle-sized topics are neglected until they become major problems. As in the knapsack problem, more clearly identifying sizes (time and attention required) and values, and considering better ways to allocate space (attention available), produces better results. By encouraging persons familiar with particular issues to bid for decision-makers' attention, giving short, clear estimates of importance and complexity of the issue, and by then rewarding helpful initiative while penalizing overbids, senior decision-makers can substantially decrease the likelihood of overlooking major problems until they become crises. Now consider agent-based models of teams of workers, each with a supervisor, with problems arriving at random by a Poisson process. A problem requires certain skills and a certain number of units of effort for each needed skill. Workers have skills and various numbers of units of work they can accomplish, per skill area, per time period. In alternative versions of the model, problems may arrive at a central point where they are sent to team supervisors, or they may drift through the organization's space until they encounter a team, or there may be some group decision-making among team supervisors and an overall manager. The simplest model is one team and problems arriving directly to that team's leader; future work can expand in modular fashion. The version of the model in which problems arrive and drift through the organization's space randomly until they encounter a team that can solve them appears to approximate - and explain - the behavior of the Cohen, March and Olsen Garbage Can Model. Other, more hierarchical versions are likely to deadlock, overwhelming the managers and unnecessarily idling many of the workers, in a manner that fit intuition for certain large, tightly controlled bureaucracies. Explicitly modeling the attention required by managers and supervisors to assign problems and monitor progress would add another level of complexity and realism. This approach appears to promise a rich variety of interesting results. Presenter: Douglas A. Samuelson is a senior analyst for the Homeland Security Institute, Arlington, Virginia, and President of WINFORMS, the Washington, DC chapter of the Institute for Operations Research and the Management Sciences (INFORMS.) He has also been a Federal policy analyst, inventor, high-tech entrepreneur and executive, and university faculty member. He is perhaps best known for his popular and long-running The ORacle column in OR/MS Today. He has a D.Sc. in operations research from George Washington University. 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
[FRIAM] Call for chapter: Intelligent Complex Adaptive Systems
Speaking of books on complex adaptive systems... - Martin Original Message Subject: [alife] Call for chapter: Intelligent Complex Adaptive Systems Date: Wed, 9 Aug 2006 10:37:04 +1000 From: Ang Yang [EMAIL PROTECTED] To: [EMAIL PROTECTED] APOLOGIES FOR MULTIPLE POSTINGS * CALL FOR CHAPTERS Proposal submission deadline: August 31, 2006 Intelligent Complex Adaptive Systems Editor: Ang Yang, University of New South Wales, Australia Yin Shan, The Australian National University, Australia Publisher: Idea Group Inc. (www.idea-group.com) * Introduction The universe is a big system of systems. It has for example, ecological systems, social systems, commodity and stock market, etc. These systems are complex and constantly adapting to their environment. Many of these systems are essential to the very existence of human beings. They cannot be fully understood by isolating their components or applying simple cause and effect reasoning due to the complexity and intensive interactions among these components. These systems can be examined by looking for patterns within their behaviour. The Complex Adaptive Systems (CAS) research uses systemic inquiry to build multi-level and multi-disciplinary representations of reality to study these systems. Recently, it has been a focus across a number of disciplines. The Overall Objective of the Book = The use of the theory of CAS is prevalent in most areas of scientific endeavour. However, most papers on the application of CAS are scattered around in different journals and conference proceedings. As such, journal and conference publications tend to focus on a very special and narrow topic. It is therefore vital to have a book which summarizes the state-of-art in this highly-evolving area. This special volume will consist of open-solicited and invited papers written by leading researchers in the field. All papers will go through a peer review process by at least three recognised reviewers and one of the editors. The book will cover the foundation as well as the practical side of the topic. This represents a balance between technicality of specialists, and readability of a larger audience. This work will raise the profile of the contribution that complex adaptive systems can make toward better understanding of the various critical systems around us. In doing so, this work should encourage both further research into this area and also the practical implementation of the results derived from this area. The Target Audience === Researchers working in the field of complex adaptive systems and related fields such as machine learning and artificial intelligence, multi-agent systems, data mining, as well as professionals in related applications such as defence, bioinformatics and sociology will find this book an indispensable state-of-art reference. Because of the comprehensive coverage of the book, the book can also be used as a text at the post-graduate level. Recommended topics include, but are not limited to, the following: == .Theory of Complex Adaptive Systems .Complex Adaptive System Tools o Network Theory o Multi-Agent Systems o Learning Methods o Simulation Models o Evolutionary Game o Data Mining and Data Farming o Visualization and Virtual Environments .Applications o Ecosystem o Economic systems (market, finance, stock market) o Energy (e.g. power grid) o Bioinformatics (e.g. genomics) o Health (e.g. epidemiology) o Sociology (e.g. social networks) o Defence and homeland security Submission Procedure Researchers and practitioners are invited to submit on or before August 15, 2006, a 2-5 page manuscript proposal clearly explaining the mission and concerns of the proposed chapter. Authors of accepted proposals will be notified by September 15, 2006 about the status of their proposals and sent chapter organizational guidelines. Full chapters are expected to be submitted by December 15, 2006. All submitted chapters will be reviewed on a double-blind review basis. The book is scheduled to be published by Idea Group Inc., www.idea-group.com, publisher of the Idea Group Publishing, Information Science Publishing, IRM Press, CyberTech Publishing and Idea Group Reference imprints. Timeline August 31, 2006: Chapter proposal due September 15, 2006: Notifying authors of acceptance/rejection of the proposal December 15, 2006: Full chapter due February 15, 2007: Notifying authors for revision February 15, 2007:
Re: [FRIAM] Simulation and policy-making
On 8/9/06, McNamara, Laura A [EMAIL PROTECTED] wrote: Computational social science doesn't lend itself to VV the way that physics-based mod-sim does, so creativity in VV is required...I agree, and I think the approach that RAND take is as good as any. My concern though is that any social science model is inevitably subjective at a deep, deep level. You want a simulation that shows it's a good idea to invade Iraq? No problem, I'll interview a bunch of experts, code up realistic micro-rules and give you a simulation that shows yes, that's a sensible policy. You want a simulation that shows it's not a good idea to invade Iraq? No problem, I'll just interview a different set of experts, get some different micro-rules in there and voila, I've shown invasion is a Bad Thing. Like I said, I'm getting more and more convinced that social science ABMs just project the prejudices of their authors/funders. Or does anyone have an example of an objective 'uncorrupted' social science ABM? Robert 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
[FRIAM] Kinds of complexity
As a followup to an on-line discussion, the face-to-face FRIAM group last week spoke some more about kinds of complexity. I mentioned a paper of Seth Lloyd's, which is called "Measures of Complexity: A non-exhaustive list." I have a hard copy, undated, and retrieved from Joe Traub's files,. I have no idea if this brief note has been published elsewhere. (Joe remembers its first appearance as "31 Flavors of Complexity" with a jokey little nod to Baskin-Robbins.)Anyway, it begins: "Recently, measures of complexity have multiplied rapidly. Some take this proliferation as a sign that no one knows what complexity really is. In fact, asking for the true mathematical definition of complexity today is like asking for the true mathematical definition of electricity in 1800: to understand electricity, it turned out to be much more productive to define several quantities, such as charge, current, voltage, inductance, etc., that could be related by simple formulas, than to define a single mathematical definition of electricity. In addition, like H and B , a number of quantities that originally were thought to describe different effects, later were discovered to be closely related, and in many circumstances, identical. The many definitions of complexity stand in similarly close relations to each other. This list groups measures that are in some situations closely related to each other, or identical."He then lists 5 groupings of kinds of complexity which seem related to each other, along with subgroups. The large groupings are information, mutual and conditional information, computational complexity, distinguishability, and definitions without precise mathematical _expression_.In short, the field is in its infancy. We force it into premature adulthood at our own cost.Pamela I sit in one of the dives On Fifty-second Street Uncertain and afraid As the clever hopes expire Of a low dishonest decadeW. H. Auden 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
Re: [FRIAM] Simulation and policy-making
Quoting Robert Holmes [EMAIL PROTECTED]: You want a simulation that shows it's a good idea to invade Iraq? No problem, I'll interview a bunch of experts, code up realistic micro-rules and give you a simulation that shows yes, that's a sensible policy. You want a simulation that shows it's not a good idea to invade Iraq? No problem, I'll just interview a different set of experts, get some different micro-rules in there and voila, I've shown invasion is a Bad Thing. Two ways to deal with that problem. 1) Data Experts can suggest micro-rules, but then provide examples when those micro- rules were used and other cases where different micro-rules were used, and historical accounts of what happened in each case. In other words do retrodiction on a past similar system that had a known result. If there are no such systems, and no way to change plans or modify a plan (based on early data), then indeed the forecasts are suspect and vulnerable to manipulation. 2) Peer review Not all experts will agree on micro-rules. Get a range of micro-rules from different experts and compute the range of possibility for all of them. Marcus 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
Re: [FRIAM] **tomorrow** Lecture: Wed Aug 9 2p, Douglas Samuelson: Attention Allocation in OrganizationalDecision-Making
What results when the people with power poke their noses into the process, any time, anywhere is second guessing, distrust, fear, and resistance. Those with power need to allocate decision making authority and then stick by that allocation, even when it comes to restricting their own behavior. That's how you get responsive organizational systems. -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Phil Henshaw Sent: Tuesday, August 08, 2006 10:57 PM To: 'The Friday Morning Applied Complexity Coffee Group' Subject: Re: [FRIAM] **tomorrow** Lecture: Wed Aug 9 2p, Douglas Samuelson: Attention Allocation in OrganizationalDecision-Making I can't believe anyone talks this way. With all due respect for the offices and life and death issues sometimes involved, you need responsive systems, not micro-managed decision makers. What you want is for the people with the ultimate responsibility to be free to poke their noses into the process, any time, any where, at their leisure. Phil Henshaw .·´ ¯ `·. ~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Stephen Guerin Sent: Tuesday, August 08, 2006 4:17 PM To: friam@redfish.com Subject: [FRIAM] **tomorrow** Lecture: Wed Aug 9 2p,Douglas Samuelson: Attention Allocation in OrganizationalDecision-Making ** tomorrow** TITLE: Attention Allocation in Organizational Decision-Making SPEAKER: Douglas A. Samuelson AFFILIATION: Homeland Security Institute LOCATION: 624 Agua Fria Conference Room TIME: Wed August 9, ** 2:00p ** (non-standard time) ABSTRACT: Consider how to improve organizational decision-making by streamlining the process of seeking and allocating the attention of top decision-makers. These decision-makers try to optimize the value they receive by allocating their attention, taking uncertainty into account. In fact, optimizing the benefits of attention results, for the organization's original problem, in the well-known satisficing behavior described by Herbert Simon. In practice, the behavior is often similar to the greedy heuristic for the knapsack problem: a few of the largest topics and many small topics get addressed, while most middle-sized topics are neglected until they become major problems. As in the knapsack problem, more clearly identifying sizes (time and attention required) and values, and considering better ways to allocate space (attention available), produces better results. By encouraging persons familiar with particular issues to bid for decision-makers' attention, giving short, clear estimates of importance and complexity of the issue, and by then rewarding helpful initiative while penalizing overbids, senior decision-makers can substantially decrease the likelihood of overlooking major problems until they become crises. Now consider agent-based models of teams of workers, each with a supervisor, with problems arriving at random by a Poisson process. A problem requires certain skills and a certain number of units of effort for each needed skill. Workers have skills and various numbers of units of work they can accomplish, per skill area, per time period. In alternative versions of the model, problems may arrive at a central point where they are sent to team supervisors, or they may drift through the organization's space until they encounter a team, or there may be some group decision-making among team supervisors and an overall manager. The simplest model is one team and problems arriving directly to that team's leader; future work can expand in modular fashion. The version of the model in which problems arrive and drift through the organization's space randomly until they encounter a team that can solve them appears to approximate - and explain - the behavior of the Cohen, March and Olsen Garbage Can Model. Other, more hierarchical versions are likely to deadlock, overwhelming the managers and unnecessarily idling many of the workers, in a manner that fit intuition for certain large, tightly controlled bureaucracies. Explicitly modeling the attention required by managers and supervisors to assign problems and monitor progress would add another level of complexity and realism. This approach appears to promise a rich variety of interesting results. Presenter: Douglas A. Samuelson is a senior analyst for the Homeland Security Institute, Arlington, Virginia, and President of WINFORMS, the Washington, DC chapter of the Institute for Operations Research and the Management Sciences (INFORMS.) He has also been a Federal policy analyst, inventor, high-tech entrepreneur
Re: [FRIAM] Kinds of complexity
On 8/9/06, Pamela McCorduck [EMAIL PROTECTED] wrote: snip...In fact, asking for the true mathematical definition of complexity today is like asking for the true mathematical definition of electricity in 1800: to understand electricity, it turned out to be much more productive to define several quantities, such as charge, current, voltage, inductance, etc. At least those scientists had the good sense to give these quantities different names. We just call each of our disparate quantites 'complexity' and then wonder why we can't get any equations to work. Robert 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
[FRIAM] Fwd: http://web.mit.edu/esd.83/www/notebook/Complexity.PDF
Seth Lloyd's paper about measures of complexity is on the web, and here's the link:http://web.mit.edu/esd.83/www/notebook/Complexity.PDF I sit in one of the dives On Fifty-second Street Uncertain and afraid As the clever hopes expire Of a low dishonest decadeW. H. Auden 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
Re: [FRIAM] Simulation and policy-making
Phil,Not quite, unfortunately. EpiSims, and other similar ABMs can all too easily be used to identify weaknesses and potential exploits of social infrastructures. We did studies for the US DHS that demonstrated exactly this a couple of years ago when I still worked at LANL. One example was when we simulated the release of a weaponized aerosol pneumonic plague disease agent in a certain busy subway station during a simulated rush hour in a simulated Chicago with a simulated population of 6.2 million people...--DougOn 8/9/06, Phil Henshaw [EMAIL PROTECTED] wrote: Those who want to use the tools of systems inquiry for secretly generating new kinds of weapons for central authorities to interfere with what interests them, won't actuallylearn much and will cause great harm. Phil Henshaw .·´ ¯ `·.~~~680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com -Original Message-From: [EMAIL PROTECTED] [mailto: [EMAIL PROTECTED]] On Behalf Of Douglas RobertsSent: Tuesday, August 08, 2006 9:40 PMTo: The Friday Morning Applied Complexity Coffee GroupSubject: Re: [FRIAM] Simulation and policy-makingRe: simulation and policy-making, a project that my group is working on at the request of the current Washington administration is helping to do just that. At the request of a consortium of representatives from the White House, Dept of Treasury, DHS, Dept. of State, and a few other cabinet-level political types, we have run numerous simulation experimental designs to establish the bounds of the effectiveness of various intervention strategies for containing an H5N1 pandemic, should it occur in the US. We are using three simulation codes: EpiSims, Epicast, and one from the Imperial College in the UK. The name of the project is Models of Infectious Disease Agent Study (MIDAS), and it is funded by NIH. See http://www.hsph.harvard.edu/press/releases/press02202006.html andhttp://usinfo.state.gov/gi/Archive/2005/Aug/08-339612.htmlor do a google search on MIDAS bird flu policy for more info.--Doug On 8/8/06, Robert Holmes [EMAIL PROTECTED] wrote: Oh I thank RAND are probably plenty ambitious in what they simulate for the US govt. Just check out their research areas: http://www.rand.org/research_areas/ Robert On 8/8/06, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote: Quoting Robert Holmes [EMAIL PROTECTED]: So if 'valid' simulations are being used to give the 'wrong' answers, what does that tell us about simulation? Is there ever any hope of objectivity (I'll give away the answer to that: no) or do all social simulations - political or economic - inevitably reflect the prejudices of their author or funder?Validated simulations, by definition, reproduce something that the authors (or funders) deem relevant as a performance metric.But that's not a problem withmodels or simulations, assuming the metrics are documented.If the authors orfunders are prone to choosing easy, low dimensional things to fit, they just need to be more ambitious.FRIAM Applied Complexity Group listservMeets Fridays 9a-11:30 at cafe at St. John's Collegelectures, archives, unsubscribe, maps at http://www.friam.org FRIAM Applied Complexity Group listservMeets Fridays 9a-11:30 at cafe at St. John's Collegelectures, archives, unsubscribe, maps at http://www.friam.org -- Doug Roberts, RTI International[EMAIL PROTECTED] [EMAIL PROTECTED]505-455-7333 - Office505-670-8195 - Cell FRIAM Applied Complexity Group listservMeets Fridays 9a-11:30 at cafe at St. John's Collegelectures, archives, unsubscribe, maps at http://www.friam.org-- Doug Roberts, RTI International[EMAIL PROTECTED][EMAIL PROTECTED] 505-455-7333 - Office505-670-8195 - 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
Re: [FRIAM] Friam Digest, Vol 38, Issue 3
Well that curve is the clearest kind of complex systems inforation we ever get. This is one beautiful and dramatic bullet of information, and I think if we ask a hundred systems scientists what it means we'll get a lot of opinion, much of it not based on systems theory. I think what's amazing about the curve is that it shows a remarkably clear dynamic in the trust of the nation, a long period on the same path of decay. What I read it as, and others may differ, is that out trust in war as a response to terror actually never had a growth, climax or stability period, only a decay period. Growth curves are usually direct evidence of the regular organizational development processes of complex systems. I think we should include using them to locate physical examples of the phenomena we wish to model, as one means of finding windows into seeing how they actually work. Phil Henshaw .·´ ¯ `·. ~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Marcus G. Daniels Sent: Wednesday, August 09, 2006 1:37 AM To: The Friday Morning Applied Complexity Coffee Group Subject: Re: [FRIAM] Friam Digest, Vol 38, Issue 3 Phil Henshaw wrote: What do you think the amazing shape of the Bush approval curve means, about the complex system events of American politics? http://jackman.stanford.edu/blog/?p=74 I rate this as very high quality data on a very real but unnoticed large scale complex system behavior. What do you see it as. It might show that people prefer to follow rather than think. 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 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
[FRIAM] gintis's Game Theory Evolving
Hi, Has anybody any thoughts to share about Gintis's new book? I have like some of Gintis's work as presented at conferences. But I am struggling with this book because, despite an aura of userfriendliness, the book seems to leave huge steps out. It seems to be a compilation of dozens and dozens of games with groovy names and silly stories.Is this what game theory IS whenone gets close to it?Is it true that game theory consists of story upon story as counterintuitive as the prisonner's dilemma game story. ( To "cooperate" means to me to be a "cooperative" witness; to defect, would be to renege on an agreement with the DA to cooperate; teaching students what these words mean to game theorists is like making them drink Jamestown Kookaid;). I have learned that there are more categories of games I have to worry about, and I suppose that is good. I have learned that there are simultaneous games in which the players move at the same moment and serial games in which one player moves and then the other. Also there are symetrical games in which, for instance your payoff playing strategy A with me is the same as my strategy playing Strategy A with you. So, I have learned that the game I have spent most time thinking about ... Tragedy of the Commons type games lke PD games.are actually a narrow category of games, Simultaneous, symetrical, two player games. (Please dont hesitate to correct me on any of this) So, I wondering, within the scope of simultaneous symmetrical two player games, are there a zillion games that differ only in subtle changes in their payoff tables AND in their groovy names and silly stories? Could all of this be collapsed into a 4d space (one dimension for each value in a 2x2 table and the space analysed? The goal would be to identify interesting regions in this space. I understand about the importance of metaphors in science and about the value of "surplus meaning" in models, even including the stuff which is just plain facetious. I KNOW that one cannot disprove Darwinism by demonstrating that there is no great FarmerInTheSky called NATURE who is doing the "selecting". But if this game theory literature is as it appears in Gintis's book, is it not surplus meaning gone wild Feel free to jerk on my chain here: I justdont get it. Nick Nicholas Thompson [EMAIL PROTECTED] EarthLink Revolves Around You. 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
