Event Detail

This talk focuses on the following question: Does recent Bayesian psychological research vindicate the contention that human cognition is rational? Addressing this question in the affirmative turns on resolving two challenges:

1. The In Principle Challenge concerns how best – in light of well-known computational complexity results – to characterize Bayesian norms so that they are, at least in principle, satisfiable by bounded human agents.

2. The Empirical Challenge concerns the extant to which Bayesian psychological research supports the contention that human cognition in fact satisfies relevant Bayesian norms of rationality.

In this talk, I discuss both these Challenges. The first part of the talk provides a partial response to the In Principle Challenge by sketching a broadly Bayesian conception of rational norms for bounded agents. The remainder of the talk focuses on the Empirical Challenge. This is an expansive issue, and I do not pretend to resolve the matter here. Rather, I first set out the challenge in a bit more detail, paying special attention to one major problem for Bayesian claims about the extent of human rationality –the apparently pervasive evidence for probability matching. Finally, I critically assess some of the main ways in which Bayesians might seek to address the problem posed by probability matching. (This is joint work with Shaun Nichols.)