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A Study on Emergence of Game and dynamical Complexity by Covpled Dynamical Recog

利用Covpled动态识别研究博弈的出现和动态复杂性

基本信息

批准号：
11837003
负责人：
IKEGAMI Takashi
金额：
$ 2.3万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2000
项目状态：
已结题

项目摘要

The aim of this project was to propose a new model framework to study evolution and cognition dynamics. Some main results are the followings.1. We have studied a model of game players who play a game by generating other player's model by a dynamical recognizer. Based on this model, the prisoner's dilemma game, the Dubey game and artificial discourse dynamics are simulated. We have also discussed an extended version of the Turing test in terms of dynamical systems.2. We have proposed and analyzed a new game system, in which the rule and the strategy are expressed by λ sentences. Since λ calculus doesn't distinguish between rules and startegies, a meta-game system is naturally treated in this system in the sense that rules and strategies can interfer with each other.3. We have studied and analyzed temporal evolution of discourse system based on a coupled dynamical recognizer. This is the first mathematical studies on discourse dynamics and the results will be published within this year.4. A distinction between a rule and a strategy in a game and between syntax and semantics in discourse interaction have been studied by giving the distinction from without. Here we have basically studied the synthetic nature of distinction itself in various systems. Other systems such as membranes and the internal chemical reaction and self/non-self disction of an immune network are studied as well. One of the important aspect both in evolution and cognition is evolvability. I have discussed it intensively.All the work I have done is related to the main theme of complex systems study called Synthetic Complexity. This is the complexity essentially generated from interactions. We should further work on this concept to build a new theoretical framework for evolution and cognition.

该项目的目的是提出一个新的模型框架来研究进化和认知动力学。主要结果如下：1.我们研究了一个由动态识别器生成其他参与者模型的参与者模型。在此模型的基础上，模拟了囚徒困境博弈、杜比博弈和人工话语动力学。我们还讨论了一个扩展版本的图灵测试的动力系统。2.本文提出并分析了一种新的博弈系统，该系统的规则和策略都用λ语句来表示。由于λ演算不区分规则和策略，因此在元博弈系统中，规则和策略可以相互干扰.研究和分析了基于耦合动态识别器的话语系统的时间演化。这是第一个关于话语动力学的数学研究，研究结果将在今年内发表。通过对规则与策略的区分，以及语篇互动中句法与语义的区分，研究了游戏中规则与策略的区别。在这里，我们基本上研究了区别本身在各种体系中的综合性质。其他系统，如膜和免疫网络的内部化学反应和自我/非自我dispersion也进行了研究。进化和认知的一个重要方面是可进化性。我所做的一切工作都与复杂系统研究的主题综合复杂性有关。这是复杂性本质上产生于相互作用。我们应该进一步研究这一概念，以建立一个新的进化和认知的理论框架。