If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Abstract: This report presents a language, called QA4, designed to facilitate the construction of problem-solving systems used for robot planning, theorem proving, and automatic program synthesis and verification. Thus it provides many useful programming aids. More importantly, however, it provides a semantic framework for common sense reasoning about these problem domains. The interpreter for the language is extraordinarily general, and is therefore an adaptable tool for developing the specialized techniques of intuitive, symbolic reasoning used by the intelligent systems.
This paper proposes a method for handling the frame problem in representing conceptual, or natural-language-type information. The method is part of a larger calculus for expressing conceptual information, called P c F-2, which is described in Sandewall (1972), and which is a modification and extension of Sandewall (1971a). When the STRIPS schema adds a fact, PLANNER would add the corresponding fact to the data base using the primitive thassert. In this context, by epistemological information we mean a notation together with a set of rules (for example, logical axioms) which describe permissible deductions.
We were led to this comparison by the observation that the computer model is weaker in three important ways: search depth is not unbounded, structures matching variables cannot be compared, and structures matching variables cannot be moved. Thus, every recursively enumerable language is generated by a transformational grammar with limited search depth, without equality comparisons of variables, and without moving structures corresponding to variables. On the other hand, both mathematical models allow unbounded depth of analysis; both allow equality comparisons of variables, although the Ginsburg-Partee model.compares
In forming such a view the Council has available to it a great deal of specialist information through its structure of Boards and Committees-- particularly from the Engineering Board and its Computing Science Committee and from the Science Board and its Biological Sciences Committee. To supplement the important mass of specialist and detailed information available to the Science Research Council, its Chairman decided to commission an independent report by someone outside the Al eld but with substantial general experience of research work in multidisciplinary elds including elds with mathematical, engineering and biological aspects. Such a personal view of the subject might be helpful to other lay persons such as Council members in the process of preparing to study specialist reports and recommendations and working towards detailed policy formation and decision taking. In scientic applications, there is a similar look beyond conventional data processing to the problems involved in large-scale data banking and retrieval, The vast eld of chemical compounds is one which has lent itself to ingenious and eective programs for data storage and retrieval and for the inference of chemical structure from mass-spec- trometry and other data.
Abstract: PLANNER is a formalism for proving theorems and manipulating models in a robot. The formalism is built out of a number of problem-solving primitives together with a hierarchical multiprocess backtrack control structure. Under BACKTRACK control structure, the hierarchy of activations of functions previously executed is maintained so that it is possible to revert to any previous state. In addition PLANNER uses multiprocessing so that there can be multiple loci of control over the problem-solving.
Language was considered just a "bunch of words" and the primary task for early machine translation (MT) was to build machines large enough to hold all the words necessary in the translation process. These means included the printing out of the several possible solutions of ambiguous text segments to let the reader decide for himself the correct meaning, printing out the ambiguous source language text, and other temporary expedients. Particularly one must understand the rules under which such a complex system as human language operates and how the mechanism of this operation can be simulated by automatic means, i.e., without any human intervention at all. The second problem, the simulation of human language behavior by automatic means, is almost impossible to achieve, since language is an open and dynamic system in constant change and because the operation of the system is not yet completely understood.
In the meantime, Chomsky (1965) devised a paradigm for linguistic analysis that includes syntactic, semantic, and phonological components to account for the generation of natural language statements. This theory can be interpreted to imply that the meaning of a sentence can be represented as a semantically interpreted deep structure--i.e, From computer science's preoccupation with formal programming languages and compilers, there emerged another paradigm. The adoption and combination of these two new paradigms have resulted in a vigorous new generation of language processing systems characterized by sophisticated linguistic and logical processing of well-defined formal data structures. These included a social-conversation machine, systems that translated from English into limited logical calculi, and programs that attempted to answer questions from English text.
This paper describes an effort to design a heuristic problem-solving program which accepts problems stated in a nondeterministic programming language and applies constraint satisfaction methods and heuristic search methods to find solutions. The use of nondeterministic programming languages for stating problems is discussed, and ref, the language accepted by the problem solver arf, is described. Various extensions to ref are considered. The conceptual structure of the program is described in detail and various possibilities for extending it are discussed.
It seems most unlikely that one could in general write purely applicative Schonfmkel descriptions', like (5), of functions already known to one in some other form. One makes assertions in the system by writing clauses, i.e., finite collections of literals considered as disjunctions of their members, universally quantified with respect to all variables. In other words, this is a first-order language in which there is only one relation symbol, namely equality; only one function symbol, namely application; and a collection of individual constants. In particular the resolution principle may be used as sole principle; or the resolution principle together with paramodulation (Robinson and Wos 1969); or Sibert's system (Sibert 1969); or the E-resolution system of Morris (1969).