In the Newcomb problem, the standard arguments for taking either one box or both boxes adduce what seem to be relevant considerations, but they are not complete arguments, and attempts to complete the arguments rely upon incorrect principles of rational decision making. It is argued that by considering how the predictor is making his prediction, we can generate a more complete argument, and this in turn supports a form of causal decision theory.

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)

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)

OSCAR is a fully implemented architecture for a cognitive agent, based largely on the author’s work in philosophy concerning epistemology and practical cognition. The seminal idea is that a generally intelligent agent must be able to function in an environment in which it is ignorant of most matters of fact. The architecture incorporates a general-purpose defeasible reasoner, built on top of an efficient natural deduction reasoner for first-order logic. It is based upon a detailed theory about how the various aspects (...) of epistemic and practical cognition should interact, and many of the details are driven by theoretical results concerning defeasible reasoning. The architecture is easily extensible by changing the set of inference schemes supplied to the reasoner. Existing inference schemes handle many kinds of epistemic cognition, including reasoning from perceptual input, causal reasoning and the frame problem, and reasoning defeasibly about probabilities. Work is underway to implement a system of defeasible decisiontheoretic planning. (shrink)

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)