具有先验信念和市场反馈的有限理性决策的极大熵模型
A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback
摘要：
有限理性是一个重要的考虑因素，因为智能体的处理能力往往有限，使得完美理性的假设不适用于许多实际任务。我们提出了一个信息理论的方法来推断代理决策史密斯竞争。该模型明确地捕捉代理的有界性（有限的信息处理能力）作为信息获取的成本，以扩大他们的先验信念。扩展被测量为后验决策和先验信念之间的Kullblack-Leibler分歧。当信息获取是免费的，经济人代理恢复，而在情况下，当信息获取变得昂贵，代理，而不是恢复到他们以前的信念。最大熵原理是用来推断最少偏置的决定的基础上正式的量子响应统计均衡框架内的史密斯竞争的概念。将先前的信念纳入这样一个框架，使我们能够系统地探讨在市场反馈的存在下，先前的信念对决策的影响，以及重要的是增加了一个时间解释的框架。我们使用澳大利亚住房市场数据验证了所提出的模型，显示了先验知识的引入如何改变所产生的代理决策。具体来说，它允许分离过去的信念和效用最大化行为的代理，以及分析到代理信念的演变。
英文摘要：
Bounded rationality is an important consideration stemming from the fact that agents often have limits on their processing abilities, making the assumption of perfect rationality inapplicable to many real tasks. We propose an information-theoretic approach to the inference of agent decisions under Smithian competition. The model explicitly captures the boundedness of agents (limited in their information-processing capacity) as the cost of information acquisition for expanding their prior beliefs. The expansion is measured as the Kullblack-Leibler divergence between posterior decisions and prior beliefs. When information acquisition is free, the homo economicus agent is recovered, while in cases when information acquisition becomes costly, agents instead revert to their prior beliefs. The maximum entropy principle is used to infer least-biased decisions based upon the notion of Smithian competition formalised within the Quantal Response Statistical Equilibrium framework. The incorporation of prior beliefs into such a framework allowed us to systematically explore the effects of prior beliefs on decision-making in the presence of market feedback, as well as importantly adding a temporal interpretation to the framework. We verified the proposed model using Australian housing market data, showing how the incorporation of prior knowledge alters the resulting agent decisions. Specifically, it allowed for the separation of past beliefs and utility maximisation behaviour of the agent as well as the analysis into the evolution of agent beliefs.
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