In L. Steels (Ed.), Advances in natural language processing. Antwerp, Belgium: University of Antwerp.

Publication 29, Institute of Linguistics, University of Stockholm.

IEEE Transwactions on Systems, Man and Cybernetics SMC-5, pp. 409-425

The alpha-beta technique for searching game trees is analyzed, in an attempt to provide some insight into its behavior. The first portion of this paper is an expository presentation of the method together with a proof of its correctness and a historical discussion. The alpha-beta procedure is shown to be optimal in a certain sense, and bounds are obtained for its running time with various kinds of random data.

This report describes progress in the development of an interactive computer program, termed MYCIN, that uses the clinical decision criteria of experts to advise physicans who request advice regarding selection of appropriate antimicrobial therapy for hospital patients with bacterial infections. Since patients with infectious diseases often require therapy before complete information about the organism becomes available, infectious disease experts have identified clinical and historical criteria that aid in the early selection of antimicrobial therapy. MYCIN gives advice in this area by means of three subprograms: (1) A Consultation System that uses information provided by the physician, together with its own knowledge base, to choose an appropriate drug or combination of drugs; (2) An Explanation System that understands simple English questions and answers them in order to justify its decisions or instruct the user; and (3) A Rule Acquisition System that acquires decision criteria during interactions with an expert and codes them for use during future consultation sessions. A variety of human engineering capabilities have been included to heighten the program's acceptability to the physicians who will use it. Early experience indicates that a sample knowledge base of 200 decision criteria can be used by MYCIN to give appropriate advice for many patients with bacteremia.

Latin, Greek, Russian, Turkish, German) the relationship of a noun phrase to the rest of a sentence is indicated by altered forms of the noun. The possible relationships are called (surface) “cases”. Because (1) it is difficult to specify semantic-free selection rules for the cases, and (2) related phenomena based on prepositions or word order appear in apparently case-less languages, many have argued that studies of cases should focus on meaning, i.e. on “deep cases”. Deep cases bear a close relationship to the modifiers of a concept. In fact, one could consider a deep case to be a special, or distinguishing, modifier.

"Optimal algorithms are derived for satisficing problem-solving search, that is, search where the goal is to reach any solution, no distinction being made among different solutions. This task is quite different from search for best solutions or shortest path solutions. Constraints may be placed on the order in which sites may be searched. This paper treats satisficing searches through partially ordered search spaces where there are multiple alternative goals." Artificial Intelligence 6:235-247.

The paper discusses the origins and structure of Preference Semantics, a procedural and computational system for extracting the meaning structure of natural language texts, based on notions of “maximal semantic density” and coherence. The basic representational structures and procedures of Preference Semantics are described, as well as the forms these notions have taken in the work of others.

We present a novel statistical approach to semantic parsing, WASP, for constructing a complete, formal meaning representation of a sentence. A semantic parser is learned given a set of sentences annotated with their correct meaning representations. The main innovation of WASP is its use of state-of-the-art statistical machine translation techniques. A word alignment model is used for lexical acquisition, and the parsing model itself can be seen as a syntax-based translation model. We show that WASP performs favorably in terms of both accuracy and coverage compared to existing learning methods requiring similar amount of supervision, and shows better robustness to variations in task complexity and word order.

Negotiation management, one such framework, has at its heart the application of computer models and related technology to a collaborative effort at dispute resolution. In this paradigm, negotiation is treated as a communicative and knowledge-intensive group problem-solving process. Easily accessible techniques are being developed for modeling both the process and substance of negotiation. In addition, tools are being designed for negotiators to use in risk and decision analysis, optimization, and precedent analysis. This paper outlines a synthesis of these elements in an integrated computer environment for negotiation management.