# About the Formal Reasoning Group

The Stanford Formal Reasoning Group concentrates on Logical AI. This is an approach to the development of symbolic AI. It was first proposed by McCarthy in his 1959 paper, Programs with Common sense. It uses logic to describe the manner in which intelligent machines or people behave.

Workers in logic-based AI hope to reach human-level intelligence with a logic-based system. Such a system, described by sentences in logic, would represent what it knew about the world in general, what it knew about the particular situation and what it knew about its goals, as proposed in Programs with Common Sense. Other data structures, e.g. for representing pictures, would be present together with programs for creating them, manipulating them and for describing them in logic. The holistic program would perform actions that it inferred were appropriate for achieving its goals.

Making a logic-based human-level program requires enough progress on at least the following problems:

## Extensions of mathematical logic

Besides nonmonotonic reasoning, other problems in the logic of AI are beginning to take a definite form, including formalization of context.

## Context

We work on formalizing contexts as first class objects. The basic relation is ist(c,p). It asserts that the proposition p is true in the context c. The most important formulas relate the propositions true in different contexts. Introducing contexts as formal objects will permit axiomatizations in limited contexts to be expanded to transcend the original limitations. This seems necessary to provide AI programs using logic with certain capabilities that human fact representation and human reasoning possess. Fully implementing transcendence seems to require further extensions to mathematical logic, i.e. beyond the nonmonotonic inference methods first invented in AI and now studied as a new domain of logic. We organized a symposium on the formalization of context as a part of the AAAI 1995 Fall Symposium Series. We also have a number of papers on this topic.

## Elaboration tolerance

The program must be able to take new facts into account to get a different solution than was suggested by the old facts. Formalized nonmonotonic reasoning was the first step toward achieving this.

## Concurrent events

Gelfond, et. al. have treated this recently using the situation calculus, and we have some recent and still unpublished results aimed at a simpler treatment.

## Intentionality

The treatment of mental objects such as beliefs (much discussed in the philosophical literature) and the corresponding term concept, e.g. ``what he thinks electrons are'' (hardly at all discussed in the formal literature).

## Reification

We need a better understanding of what are to be considered objects in the logic. For example, a full treatment of the "missionaries and cannibals" problem together with reasonable elaborations must allow us to say, ``There are just two things wrong with the boat.''

## Introspection and transcendence

Human intelligence has the ability to survey, in some sense, the whole of its activity, and to consider any assumption, however built-in, as subject to question. Humans aren't really very good at this, and it is only needed for some very high level problems. Nevertheless, we want it, and there are some ideas about how to get it.

Unfortunately, too many people concentrated on self-referential sentences. It's a cute subject, but not relevant to human introspection or to the kinds of introspection we will have to make computers do.

## Levels of description

If one is asked how an event occurred, one can often answer by giving a sequence of lower level events that answer the question for the particular occurrence. Once I bought some stamps by going to the stamp selling machine in the airport and putting in six dollars, etc. Each of these subevents has a how, but I didn't plan them, and cannot recall them. A stamp buying coach would have analyzed them to a lower level than I could and would be able to teach me how to buy stamps more effectively. For AI, we therefore, need a more flexible notion than the computer science theories of how programs are built up from elementary operations.

These problems typify the work the Formal Reasoning Group does. The group consists of Prof. John McCarthy, Tom Costello, Eyal Amir and Sasa Buvac. Sasa, Eyal and Tom are all around and their offices are Gates 216 and 218. Johns office is GATES 208.