John Pollock

Practical reasoning aims at deciding what actions to perform in light of the goals a rational agent possesses. This has been a topic of interest in both philosophy and artificial intelligence, but these two disciplines have produced very different models of practical reasoning. The purpose of this paper is to examine each model in light of the other and produce a unified model adequate for the purposes of both disciplines and superior to the standard models employed by either.The philosophical (decision-theoretic) model directs activity by evaluating acts one at a time in terms of their expected utilities. It is argued that, except in certain special cases, this constitutes an inadequate theory of practical reasoning leading to intuitively incorrect action prescriptions. Acts must be viewed as parts of plans, and plans evaluated as coherent units rather than piecemenal in terms of the acts comprising them. Rationality dictates choosing acts by first choosing the plans prescribing them. Plans, in turn, are compared by looking at their expected values. However, because plans can be embedded in one another, we cannot select plans just by maximizing expected values. Instead, we must employ a more complex criterion here named coextendability.

This chapter reiterates the proposition that practical cognition should not aim at finding optimal solutions to practical problems. A rational cognizer should instead look for good solutions, and replace them with better solutions if any are found. Solutions come in the form of plans. In general, a change to the master plan may consist of deleting several local plans and adding several others. This theory is still fairly schematic. It leaves most details to the imagination of the reader, and in philosophy, that is often a recipe for disaster. When philosophical theories fail, it is not because they did not look good in the abstract—it is because it is impossible to make the details work. This chapter simply gives a preliminary sketch of how a resource bounded agent can actually perform locally global planning.

Counterexamples are constructed for the theory of rational choice that results from a direct application of classical decision theory to ordinary actions. These counterexamples turn on the fact that an agent may be unable to perform an action, and may even be unable to try to perform an action. An alternative theory of rational choice is proposed that evaluates actions using a more complex measure, and then it is shown that this is equivalent to applying classical decision theory to "conditional policies" rather than ordinary actions.

Counterexamples are constructed for classical decision theory, turning on the fact that actions must often be chosen in groups rather than individually, i.e., the objects of rational choice are plans. It is argued that there is no way to define optimality for plans that makes the finding of optimal plans the desideratum of rational decision-making. An alternative called “locally global planning” is proposed as a replacement for classical decision theory. Decision-making becomes a non-terminating process without a precise target rather than a terminating search for an optimal solution