The structure of adaptive competition in minority games
The structure of adaptive competition in minority games
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少数民族博弈中的自适应竞争结构
DOI：
10.1016/s0378-4371(00)00100-x
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发表时间：
1998
影响因子：
3.3
通讯作者：
Mary
中科院分区：
文献类型：
--
作者：
R. Manuca;Yi Li;R. Riolo;Robert Savit Program for Study of Complex Systems;U. Michigan;Physics Dept.;College of William;Mary
在本文中，我们提出的结果和分析的一类游戏中，异质代理人的奖励是在一个少数群体。每个代理人都拥有许多固定的策略，每个策略都是下一个少数群体的预测因子。这些策略使用一组聚合的、公开可用的信息（反映了智能体的集体先前决策）来进行预测。一个智能体通过使用他的一个策略来选择在给定时刻加入哪个组。这些游戏是自适应的，因为代理人可以在游戏的不同点选择，在选择加入哪个组时使用不同的策略。博弈不是进化的，因为代理人的策略在博弈开始时是固定的。我们发现，而一般来说，这样的系统证据的阶段变化，从一个适应不良，信息效率高的阶段，系统在产生资源的表现不佳，一个低效的阶段，其中有一个紧急的合作代理之间，系统更有效地产生资源。最佳紧急协调是在这两个阶段之间的过渡区域中实现的。当策略空间的维度与玩游戏的代理数量级相同时，就会发生这种转变。我们提出了这种一般行为的解释，部分基于信息理论分析的系统及其公开信息。我们还提出了一个平均场模型的游戏，这是最准确的适应不良，有效的阶段。此外，我们表明，在两个不同的阶段，最好的个人代理的性能是通过具有显着不同的特点的策略集。我们讨论的影响，我们的研究结果的各个方面的复杂适应系统的研究。
In this paper we present results and analyses of a class of games in which heterogeneous agents are rewarded for being in a minority group. Each agent possesses a number of fixed strategies each of which are predictors of the next minority group. The strategies use a set of aggregate, publicly available information (reflecting the agents’ collective previous decisions) to make their predictions. An agent chooses which group to join at a given moment by using one of his strategies. These games are adaptive in that agents can choose, at different points of the game, to exercise different strategies in making their choice of which group to join. The games are not evolutionary in that the agents’ strategies are fixed at the beginning of the game. We find, rather generally, that such systems evidence a phase change from a maladaptive, informationally efficient phase in which the system performs poorly at generating resources, to an inefficient phase in which there is an emergent cooperation among the agents, and the system more effectively generates resources. The best emergent coordination is achieved in a transition region between these two phases. This transition occurs when the dimension of the strategy space is of the order of the number of agents playing the game. We present explanations for this general behavior, based in part on an information theoretic analysis of the system and its publicly available information. We also propose a mean-field-like model of the game which is most accurate in the maladaptive, efficient phase. In addition, we show that the best individual agent performance in the two different phases is achieved by sets of strategies with markedly different characteristics. We discuss implications of our results for various aspects of the study of complex adaptive systems.