AGAINST OPTIMALITY: LOGICAL FOUNDATIONS FOR DECISION‐THEORETIC PLANNING IN AUTONOMOUS AGENTS
John L. Pollock · Computational Intelligence · 2006
This paper investigates decision‐theoretic planning in sophisticated autonomous agents operating in environments of real‐world complexity. An example might be a planetary rover exploring a largely unknown planet. It is argued that existing algorithms for decision‐theoretic planning are based on a logically incorrect theory of rational decision making. Plans cannot be evaluated directly in terms of their expected values, because plans can be of different scopes, and they can interact with other previously adopted plans. Furthermore, in the real world, the search for optimal plans is completely intractable. An alternative theory of rational decision making is proposed, called “locally global planning.”