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Bounded rationality in agent-based models: experiments with evolutionary programs

机译：基于主体的模型中的有限理性：进化程序的实验

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This paper examines the use of evolutionary programming in agent-based modelling to implement the theory of bounded rationality. Evolutionary programming, which draws on Darwinian analogues of computing to create software programs, is a readily accepted means for solving complex computational problems. Evolutionary programming is also increasingly used to develop problem-solving strategies in accordance with bounded rationality, which addresses features of human decision-making such as cognitive limits, learning, and innovation. There remain many unanswered methodological and conceptual questions about the linkages between bounded rationality and evolutionary programming. This paper reports on how changing parameters in one variant of evolutionary programming, genetic programming, affects the representation of bounded rationality in software agents. Of particular interest are: the ability of agents to solve problems; limits to the complexity of agent strategies; the computational resources with which agents create, maintain, or expand strategies; and the extent to which agents balance exploration of new strategies and exploitation of old strategies.
机译：本文探讨了在基于主体的建模中使用进化规划来实现有限理性的理论。进化编程利用了达尔文的计算类似物来创建软件程序，是解决复杂计算问题的一种容易接受的方法。进化编程也越来越多地用于根据有限理性来开发解决问题的策略，该策略解决了人类决策的特征，例如认知极限，学习和创新。关于有限理性与进化规划之间的联系，仍然存在许多未解决的方法论和概念性问题。本文报道了在进化编程的一种变体（遗传编程）中如何更改参数如何影响软件代理中有限理性的表示。特别令人感兴趣的是：代理商解决问题的能力；限制代理策略的复杂性；代理用来创建，维护或扩展策略的计算资源；代理商在多大程度上平衡了对新策略的探索和对旧策略的利用。

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