John Pollock

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.

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.

The contributions in this volume make an important effort to resurrect a rather old fashioned form of foundationalism. They defend the position that there are some beliefs that are justified, and are not themselves justified by any further beliefs. This epistemic foundationalism has been the subject of rigorous attack by a wide range of theorists in recent years, leading to the impression that foundationalism is a thing of the past. DePaul argues that it is precisely the volume and virulence of the assaults which points directly to the strength and coherence of the position

When your word processor or email program is running on your computer, this creates a “virtual machine” that manipulates windows, files, text, etc. What is this virtual machine, and what are the virtual objects it manipulates? Many standard arguments in the philosophy of mind have exact analogues for virtual machines and virtual objects, but we do not want to draw the wild metaphysical conclusions that have sometimes tempted philosophers in the philosophy of mind. A computer file is not made of epiphenomenal ectoplasm. I argue instead that virtual objects are “supervenient objects.” The stereotypical example of supervenient objects is the statue and the lump of clay. To this end I propose a theory of supervenient objects. Then I turn to persons and mental states. I argue that my mental states are virtual states of a cognitive virtual machine implemented on my body, and a person is a supervenient object supervening on this cognitive virtual machine.

Epistemology is about how we can know the various things we claim to know. Epistemology is driven by attempts to answer the question, “How do you know?” This gives rise to investigations on several different levels. At the lowest level, philosophers investigate particular kinds of knowledge claims. Thus we find theories of perceptual knowledge (“How do you know the things you claim to know directly on the basis of perception?”), theories of induction and abduction (“How do you know the general truths you infer from observation of particular cases?”), theories of our knowledge of other minds, theories of mathematical knowledge, and so forth. At an intermediate level, topics are investigated that pertain to all or most of the specific kinds of knowledge discussed at the lowest level. Theories of reasoning, both deductive and defeasible, occur at this level. At the highest level we find general epistemological theories that attempt to explain how knowledge in general is possible. At this level we encounter versions of foundationalism, coherentism, probabilism, reliabilism, and direct realism. One can be doing epistemology by working at any of these levels. The levels cannot be isolated from each other, however. Work at any level tends to presuppose something about the other levels. For example, work on inductive reasoning at least presupposes that reasoning plays a role in the acquisition or justification of beliefs and normally presupposes something about the structure of defeasible reasoning.

I argue here that sophisticated AI systems, with the exception of those aimed at the psychological modeling of human cognition, must be based on general philosophical theories of rationality and, conversely, philosophical theories of rationality should be tested by implementing them in AI systems. So the philosophy and the AI go hand in hand. I compare human and generic rationality within a broad philosophy of AI and conclude by suggesting that ultimately, virtually all familiar philosophical problems will turn out to be at least indirectly relevant to the task of building an autonomous rational agent, and conversely, the AI enterprise has the potential to throw light at least indirectly on most philosophical problems.