Probabilistic representation of complexity

We introduce a framework to study individuals' behavior in environments that are deterministic, but too complex to permit tractable deterministic representations. An agent in these environments uses a probabilistic model to cope with his inability to think through all contingencies in advance. We interpret this probabilistic model as embodying all patterns the agent perceives, yet allowing for the possibility that there may be important details he had missed. Although the implied behavior is rational, it is consistent with an agent who believes his environment is too complex to warrant precise planning, foregoes finely detailed contingent rules in favor of vaguer plans, and expresses a preference for flexibility. (C) 2003 Elsevier Science (USA). All rights reserved.