Abstract

Cognitive agents form beliefs representing the world, evaluate the world as represented, form plans for making the world more to their liking, and perform actions executing the plans. Then the cycle repeats. This is the doxastic-conative loop, diagrammed in figure one.1 Both human beings and the autonomous rational agents envisaged in AI are cognitive agents in this sense. The cognition of a cognitive agent can be subdivided into two parts. Epistemic cognition is that kind of cognition responsible for producing and maintaining beliefs. Practical cognition evaluates the world, adopts plans, and initiates action. There is a massive literature both in philosophy and artificial intelligence concerning various aspects of epistemic cognition, and large parts of it are well understood. Practical cognition is less well understood. We can usefully divide practical cognition into five parts: (1) the evaluation of the world as represented by the agent’s beliefs, (2) the adoption of goals for changing it, (3) the construction of plans for achieving goals, (4) the adoption of plans, and (5) the execution of plans. There is a substantial literature in AI concerning the construction and execution of plans, and I will say nothing further about those topics here. This paper will focus on the evaluative aspects of practical cognition. Evaluation plays an essential role in both goal selection and plan adoption. My concern here is the investigation of evaluation as a cognitive enterprise performed by cognitive agents. I am interested both in how it is performed in human beings and how it might be performed in artificial rational agents.