To summarize, in order for rational agents to be able to engage in the sophisticated kinds of reasoning exemplified by human beings, they must be able to introspect much of their cognition. The problem of other minds and the problem of knowing the mental states of others will arise automatically for any rational agent that is able to introspect its own cognition. The most that a rational agent can reasonably believe about other rational agents is that they have rational architectures (...) similar to its own, and that they have thoughts related to their rational architectures in certain ways. This leads to Rational Functionalism as an account of what it is to be a cognizer having mental states. That in turn entails that a computer can be a person in precisely the same sense as my next door neighbor if it can appropriately mimic my rational architecture. There is nothing I could know about my neighbor that I could not believe with equal justification about the computer. Rational Functionalism also makes it reasonable to define the narrow content of a thought to be its overall place in the agent's rational architecture, that is, its conceptual role. This is, however, avery narrow notion of content. For practical purposes, we are not interested in knowing the narrow contents of other people's thoughts. We are only interested in rather general properties of those narrow contents. This is what is expressed by the use ofthat-clauses in public language. (shrink)

I intend to show some of the limits of the decision-theoretic model in connection with the analysis of cognitive agency. Although the concept of maximum expected utility can be helpful for explaining the decision-making process, it is certainly not the primary motor that moves agents to action. Moreover, it has been noticed elsewhere that this model is inadequate to the analysis of single cases of practical reasoning. A theory is proposed that introduces a plan-structure as a basic idea. In order (...) to know its very conceptual scope, we need to accommodate that theory to a cognitive architecture whereby the rational and autonomous agent makes choices and deliberates between courses of action to achieve specific goals that are of its interest. The paper endeavours also to clarify the relationship between the different modules that should constitute the architecture of an agent to accomplish the requisites of efficiency and autonomy in a changeable and dynamic world. (shrink)

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. (shrink)

In its present incarnation, OSCAR is a fully implemented programmable architecture for a rational agent. If we just focus upon the epistemic reasoning in OSCAR, we have a powerful general-purpose defeasible reasoner. The purpose of this paper is to describe that reasoner. OSCAR's defeasible reasoner is based upon seven fundamental ideas. These are (1) an argument-based account of defeasible reasoning, (2) an analysis of defeat-status given a set of interrelated arguments, (3) a general adequacy criterion for automated defeasible reasoners, called (...) “d.e.-adequacy”, (4) the claim that a generalpurpose defeasible reasoner must have the kind of structure I have called “flag-based”, (5) an algorithm for computing defeat-status, (6) an interest-driven monotonic reasoner, and (7) an account of degrees of justification, degrees of interest, and their interactions. These will each be discussed in turn. (shrink)

A rational agent has beliefs reflecting the state of its environment, and likes or dislikes Its situation. When it finds the world not entirely to Its liking, it tries to change that. We can, accordingly, evaluate a system of cognition in terms of its probable success in bringing about situations that are to the agent's liking. In doing this we are viewing practical reasoning from “the design stance.” It is argued that a considerable amount of the structure of rationality can (...) be elicited as providing the only apporant solutions to various logical and feasibility problems that arise in the course of trying to design a rational agent that satisfies this design specification. (shrink)