Ascribing mental qualities like beliefs, intentions and wants to a machine is sometimes correct if done conservatively and is sometimes necessary to express what is known about its state. We propose some new definitional tools for this: definitions relative to an approximate theory and second order structural definitions.

This collection of articles and associated discussion papers focuses on a problem that has attracted increasing attention from linguists and psychologists throughout the world during the past several years. Reduced to essentials, the problem is that of discovering the character of the mental capacities that make it possible for human beings to attain knowledge of their language on the basis of fragmentary and haphazard early linguistic experience. A fundamental assumption running through all of these contributions is that people possess strong (...) innate predispositions that are critical for success in this task. (shrink)

These notes discuss formalizing contexts as first class objects. The basic relationships are: ist(c,p) meaning that the proposition p is true in the context c, and value(c,p) designating the value of the term e in the context c Besides these, there are lifting formulas that relate the propositions and terms in subcontexts to possibly more general propositions and terms in the outer context. Subcontextx are often specialised with regard to time, place and terminology. 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, ie. beyond the nonmonotonic inference methods first invented in AI and now studied as a new domain of logic. (shrink)

This article is inspired by recent psychological studies confirming that a child is not born a blank slate but has important innate capabilities. An important part of the ``learning'' required to deal with the three dimensional world of objects, processes, and other beings was done by evolution. Each child need not do this learning itself.

In AI, consciousness of self consists in a program having certain kinds of facts about its own mental processes and state of mind. We discuss what consciousness of its own mental structures a robot will need in order to operate in the common sense world and accomplish the tasks humans will give it. It's quite a lot. Many features of human consciousness will be wanted, some will not, and some abilities not possessed by humans have already been found feasible and (...) useful in limited contexts. We give preliminary fragments of a logical language a robot can use to represent information about its own state of mind. A robot will often have to conclude that it cannot decide a question on the basis of the information in memory and therefore must seek information externally. Gödel's idea of relative consistency is used to formalize non-knowledge. Programs with the kind of consciousness discussed in this article do not yet exist, although programs with some components of it exist. Thinking about consciousness with a view to designing it provides a new approach to some of the problems of consciousness studied by philosophers. One advantage is that it focusses on the aspects of consciousness important for intelligent behavior. (shrink)

We discuss first order theories in which individual concepts are admitted as mathematical objects along with the things that reify them. This allows very straightforward formalizations of knowledge, belief, wanting, and necessity in ordinary first order logic without modal operators. Applications are given in philosophy and in artificial intelligence. We do not treat general concepts, and we do not present any full axiomatizations but rather show how various facts can be expressed.

Logical AI involves representing knowledge of an agent’s world, its goals and the current situation by sentences in logic. The agent decides what to do by inferring that a certain action or course of action is appropriate to achieve the goals. We characterize briefly a large number of concepts that have arisen in research in logical AI. Reaching human-level AI requires programs that deal with the common sense informatic situation. This in turn requires extensions from the way logic has been (...) used in formalizing branches of mathematics and physical science. It also seems to require extensions to the logics themselves, both in the formalism for expressing knowledge and the reasoning used to reach conclusions. A large number of concepts need to be studied to achieve logical AI of human level. This article presents candidates. The references, though numerous, to articles concerning these concepts are still insuf- ficient, and I’ll be grateful for more, especially for papers available on the web. This article is available in several forms via http://www-formal.stanford.edu/jmc/conceptsai.html. (shrink)

Although living conditions have improved throughout history, protest, at least in the last few decades, seems to have increased to the point of becoming a normal phenomenon in modern societies. Contributors to this volume examine how and why this is the case and argue that although problems such as poverty, hunger, and violations of democratic rights may have been reduced in advanced Western societies, a variety of other problems and opportunities have emerged and multiplied the reasons and possibilities for protest.

Logical AI develops computer programs that represent what they know about the world primarily by logical formulas and decide what to do primarily by logical reasoning--including nonmonotonic logical reasoning. It is convenient to use logical sentences and terms whose meaning depends on context. The reasons for this are similar to what causes human language to use context dependent meanings. This note gives elements of some of the formalisms to which we have been led. Fuller treatments are in [McC93], [Guh91] and (...) [MB94] and the references cited in the Web page [Buv95]. The first main idea is to make contexts first class objects in the logic and use the formula ist(c,p) to assert that the proposition p is true in the context c. A second idea is to formalize how propositions true in one context transform when they are moved to different but related contexts. An ability to transcend the outermost context is needed to give computer programs the ability to reason about the totality of all they have thought about so far [McC96]. (shrink)

This article is oriented toward the use of modality in artificial intelligence (AI). An agent must reason about what it or other agents know, believe, want, intend or owe. Referentially opaque modalities are needed and must be formalized correctly. Unfortunately, modal logics seem too limited for many important purposes. This article contains examples of uses of modality for which modal logic seems inadequate.I have no proof that modal logic is inadequate, so I hope modal logicians will take the examples as (...) challenges. (shrink)

John Searle begins his ``Consciousness, Explanatory Inversion and Cognitive Science'' with " ``Ten years ago in this journal I published an article criticising what I call Strong AI, the view that for a system to have mental states it is sufficient for the system to implement the right sort of program with right inputs and outputs. Strong AI is rather easy to refute and the basic argument can be summarized in one sentence: {it a system, me for example, could implement (...) a program for understanding Chinese, for example, without understanding any Chinese at all.} This idea, when developed, became known as the Chinese Room Argument.'' " The Chinese Room Argument can be refuted in one sentence. (shrink)

internal events that happen spontaneously from external events (actions). It also treats processes, e.g. a buzzer, that do not settle down. The non-monotonic reasoning is circumscription done situation by situation.

Here's the article which was a 1964 Stanford AI Memo. After the original memo, several people offered different proofs of the theorem including Shmuel Winograd, Marvin Minsky and Dimitri Stefanyuk - none published, to my knowledge. Winograd claimed that his proof was non-creative, because it didn't use an extraneous idea like the colors of the squares. This set off a contest to see who could produce the most non-creative proof. Minsky's idea was to start with the diagonal next to an (...) excluded corner ssquare, note that 2 dominoes had to project from it to the diagonal with three squares, and from there 1 domino to the four square diagonal, etc. Coming from the other end also leaves only six of the eight squares in the long diagonal covered. Minsky's proof gets high points for non-creativity, because it is specific to the 8 by 8 board. (Using the colors it is easy to show that a Minsky style proof will work for any even sized board.). (shrink)

From the AI point of view, consciousness must be regarded as a collection of interacting processes rather than the unitary object of much philosophical speculation. We ask what kinds of propositions and other entities need to be designed for consciousness to be useful to an animal or a machine. We thereby assert that human consciousness is useful to human functioning and not just and epiphenomenon. Zombies in the sense of Todd Moody's article are merely the victims of Moody's prejudices. To (...) behave like humans, zombies will need what Moody might call pseudo-consciousness, but useful pseudo-consciousness will share all the observable qualities of human consciousness including what the zombie will be able to report. Robots will require a pseudo-consciousness with many of the intellectual qualities of human consciousness but will function successfully with few if any human emotional conscious qualities if that is how we choose to build them. (shrink)

The aim of this article is to motivate and outline a dialogical perspective on agency that accommodates centrifugal and centripetal tendencies in current cultural theories of agency. To complement approaches that assume a high degree of integration and clarity, we emphasise the diversity of agency as it is experienced in the open-ended dialogical relationship with a particular other. While these former approaches to agency provide us with the means to examine the influence of social processes such as division of labour (...) and reproduction of community, they tend to underplay the importance of agency as it is embodied and experienced in the lives of particular people. To reflect on this aspect of agency, we will draw extensively on Bakhtin's work, which crosses boundaries between philosophy, psychology and literary criticism, and which is concerned to understand what is personal in activity. In terms of agency, his work draws our attention to the sense of responsibility and potentiality that imbues our dialogues with particular others, the aesthetics and ethics involved in dialoguing with the other, and the sense of dilemmatic choice and intonation that is involved in our dialogue with the other. (shrink)

An 8 by 8 checkerboard with two diagonally opposite squares removed cannot be covered by dominoes each of which covers two rectilinearly adjacent squares. present a set theory description of the proposition and an informal proof that the covering is impossible. While no present system that I know of will accept either formal description or the proof, I claim that both should be admitted in any heavy duty set theory.

Aristotle and the shape of modern friendships. With John McCarthy and Matthew West.

My 1953 proof that the function is everywhere continuous and nowhere differentiable is just 13 lines. I've added some remarks to the note in the American Mathematical Monthly.

An Example for Natural Language Understanding and the AI Problems it Raises I think this 1976 memorandum is of 1996 interest. The problems it raises haven't been solved or even substantially reformulated.

AI needs many ideas that have hitherto been studied only by philosophers. This is because a robot, if it is to have human level intelligence and ability to learn from its experience, needs a general world view in which to organize facts. It turns out that many philosophical problems take new forms when thought about in terms of how to design a robot. Some approaches to philosophy are helpful and others are not.

• Lisp programs are Lisp data—abstract syntax. Programming languages need functions for their abstract • English is important for its semantics—not its syntax • The largest piece of cake—Kleene µ operator • An elephant never forgets and is faithful. • Resolution considered harmful. • Special provers are just strategies—Davis-Putnam • Programs as logical formulas—Algol 48 and Algol..

“...it seems that hardly anybody proposes to use different variables for propositions and for truth-values, or different variables for individuals and individual concepts.” (Carnap 1956, p. 113).

engineering—Achieve goals in the world—so study world 1. Write programs using non-logical representations. 2. represent facts about the world in logic and decide what to do by logical inference..

Apology: My knowledge of of machine learning is no more recent than Tom Mitchell's book. Its chapters describe, except for inductive logic programming, programs aimed at classifying appearances.

Elephant 2000 is a proposed programming language good for writing and verifying programs that interact with people (eg. transaction processing) or interact with programs belonging to other organizations (eg. electronic data interchange) 1. Communication inputs and outputs are in an I-O language whose sentences are meaningful speech acts identified in the language as questions, answers, offers, acceptances, declinations, requests, permissions and promises. 2. The correctness of programs is partly defined in terms of proper performance of the speech acts. Answers should (...) be truthful and responsive, and promises should be kept. Sentences of logic expressing these forms of correctness can be generated automatically from the form of the program. 3. Elephant aource programs may not need data structures, because they can refer directly to the past. Thus a program can say that an airline passenger has a reservation if he has made one and hasn't cancelled it. 4. Elephant programs themselves can be represented as sentences of logic. Their extensional properties follow from this representation without an intervening theory of programming or anything like Hoare axioms. 5. Elephant programs that interact non-trivially with the outside world can have both input-output specification, relating the programs inputs and outputs, and accomplishment specifications concerning what the program accomplishes in the world. These concepts are respectively generalizations of the philosophers' illocutionary and perlocutionary speech acts. 6. Programs that engage in commercial transactions assume obligations on behalf of their owners in exchange for obligations assumed by other entities. It may be part of the specification of an Elephant 2000 program that these obligations are exchanged as intended, and this too can be expressed by a logical sentence. 7. Human speech acts involve intelligence. Elephant 2000 is on the borderline of AI, but the article emphasizes the Elephant usages that do not require AI. (shrink)

Here are some essays written at various times. What does it mean to be rational? American History for Valley Girls The Chief Seattle Theme Park Here's a Manifesto of the Newtonian Brotherhood of Truly Christian Scientists . I regret to say that it has turned out to be necessary to explicitly characterize it as humor. I didn't mind that some careless readers accused me of being a bigot, but I had to put in a disclaimer when some readers emailed me (...) with their support for the ideas. (shrink)

The most important scientific events of the 20th century were the theory of relativity, quantum mechanics and the discovery of the genetic code. The most important engineering events were nuclear energy, which insures adequate energy for a billion years, the computer, micro-electronics, the green revolution, and the beginnings of genetic engineering. The general development of technology permits worldwide high standards of living.