Abstract
Strategy is formally defined as a complete plan of action for every contingency in a game. Ideal agents can evaluate every contingency. But real people cannot do so, and require a belief-revision policy to guide their choices in unforeseen contingencies. The objects of belief-revision policies are beliefs, not strategies and acts. Thus, the rationality of belief-revision policies is subject to Bayesian epistemology. The components of any belief-revision policy are credences constrained by the probability axioms, by conditionalization, and by the principles of indifference and of regularity. The principle of indifference states that an agent updates his credences proportionally to the evidence, and no more. The principle of regularity states that an agent assigns contingent propositions a positive (but uncertain) credence. The result is rational constraints on real people’s credences that account for their uncertainty. Nonetheless, there is the open problem of non-evidential components that affect people’s credence distributions, despite the rational constraint on those credences. One non-evidential component is people’s temperaments, which affect people’s evaluation of evidence. The result is there might not be a proper recommendation of a strategy profile for a game (in terms of a solution concept), despite agents’ beliefs and corresponding acts being rational.
Highlights
Ken Binmore [1] demarcates two modes of analysis in game theory
Epistemic game theory provides the epistemic foundations for rational justification of social behavior
The motivation behind the recent formation of naturalistic game theory does stem from dissatisfaction with the current debates over foundational concepts
Summary
Ken Binmore [1] demarcates two modes of analysis in game theory. The eductive mode (comprised of deduction, induction, and adduction) analyzes social behavior according to the strict idealizations of rational choice theory. I substitute the disciplines of epistemic and evolutionary game theory for Binmore’s modes of analysis. Evolutionary game theory establishes social behavior that is evolutionarily fit and stable. In epistemic game theory, belief-revision policies are part of those idealizations The rationality of belief-revision policies is the subject of Bayesian epistemology. The objects of analysis of belief-revision policies are epistemic states, not strategies and acts. The main claim is that foundational concepts are best understood vis-à-vis real people’s cognitive limits, which explains why analyzing said concepts in highly abstract and artificial circumstances is problematic. The charge of incoherence to backward induction is best explained by naturalism This leaves open the question of how we analyze the rationality of belief-revision policies. I place the epistemic foundations of game theory into a more foundational epistemology
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