Towards a Logical Theory of Practical Reasoning

From the very beginning, logicians have counted practical (or action-oriented) reasoning as well as theoretical (or belief-oriented) reasoning as part of their subject. However, despite a tradition that continues to the present, logicians have not produced formalisms that could be considered of any use in designing an agent that needs to act intelligently, or in helping an intelligent agent to evaluate its reasoning about action. In contrast, the decision-theoretic paradigm that grew out of the economic tradition is widely applied in many areas, including AI, and has dominated recent philosophical thinking about practical reasoning, without serious competition from the logical tradition. This lack of progress is largely due to the unavailability of qualitative mechanisms for dealing with the appropriate inference procedures. To handle even the simplest cases of practical reasoning, it is essential to deliver a reasoning mechanism that allows practical conclusions to be nonmonotonic in the agent’s beliefs. (If have decided to drive my car to work rather than to ride my bicycle, I may well want to to withdraw this conclusion on learning that the car has a fiat tire.) And, until recently, the only way to formalize inference procedures with these characteristics has been to use probability functions. Therefore, quantitative utility theory has remained about the only game in town.