J. International Computer Chess Association, 15 (1): 16-18.

The checkers program Chinook has won the right to play a 40-game match for the World Checkers Championship against Dr. Marion Tinsley. This was earned by placing second, after Dr. Tinsley, at the 1990 U.S. National Open, the biennial event used to determine a challenger for the championship. This is the first time a program has earned the right to contest for a human world championship. In an exhibition match played in December 1990, Tinsley narrowly defeated Chinook 7.5-6.5. This paper describes the program, the research problems encountered and our solutions.

Deep Blue is the chess machine that defeated then-reigning World Chess Champion Garry Kasparov in a six-game match in 1997. This paper describes the Deep Blue system, and gives some of the rationale that went into the design decisions behind Deep Blue.

In this paper we outline a general approach to the study of problem-solving, in which search steps are considered decisions in the same sense as actions in the world. Unlike other metrics in the literature, the value of a search step is defined as a real utility rather than as a quasiutility, and can therefore be computed directly from a model of the base-level problem-solver. We develop a formula for the expected value of a search step in a game-playing context using the single-step assumption, namely that a computation step can be evaluated as it was the last to be taken. We prove some metalevel theorems that enable the development of a low-overhead algorithm, MGSS*, that chooses search steps in order of highest estimated utility. Although we show that the single-step assumption is untenable in general, a program implemented for the game of Othello soundly beats an alpha-beta search while expanding significantly fewer nodes, even though both programs use the same evaluation function.

In Levy, D. and Beal, D. (Eds.), Heuristic Programming in Artificial Intelligence. Ellis Horwood.

J. International Computer Chess Association, May, 131–139.

In response to a world in which cancer is a growing global health challenge, there is now a greater need for US Medical Physicists and other Radiation Oncology professionals across institutions to work together and be more globally engaged in the fight against cancer. There are currently many opportunities for Medical Physicists to contribute to alleviating this pressing need, especially in helping enhance access to Medical Physics Education/training and Research Excellence across international boundaries, particularly for low and middle-income countries (LMIC), which suffer from a drastic shortage of accessible knowledge and quality training programs in radiotherapy. Many Medical Physicists aremore » not aware of the range of opportunities that even with small effort could have a high impact. Faculty at the two CAMPEP-accredited Medical Physics Programs in New England: the University of Massachusetts Lowell and Harvard Medical School have developed a growing alliance to increase Access to Medical Physics Education/training and Research Excellence (AMPERE), and facilitate greater active involvement of U.S. Medical Physicists in helping the global fight against cancer and cancer disparities. In this symposium, AMPERE Alliance members and partners from Europe and Africa will present and discuss the growing global cancer challenge, the dearth of knowledge, research, and other barriers to providing life-saving radiotherapy in LMIC, mechanisms for meeting these challenges, the different opportunities for participation by Medical Physicists, including students and residents, and how participation can be facilitated to increase AMPERE for global health.

A piece-of-advice suggests what goal should be achievednext while preserving some other condition. If this goal can be achieved in agiven problem-situation (e.g. a given chess position) then we say that the piece-ofadviceis 'satisfiable' in that position. In this way ALI makes it possible to breakthe whole problem of achieving an ultimate goal into a sequence of subproblems,each of them consisting of achievement of a subgoal prescribed by some pieceof-advice. The control structure which chooses what piece-of-advice to applynext consists of a set of 'advice-tables', each of them being specialized in acertain problem-subdomain.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.

Othello is a recent addition to the collection of games that have been examined within artificial intelligence. Advances have been rapid, yielding programs that have reached the level of world-championship play. This article describes the current champion Othello program, iago. The work described here includes: (1) a task analysis of Othello; (2) the implementation of a program based on this analysis and state-of-the-art AI game-playing techniques; and (3) an evaluation of the program's performance through games played against other programs and comparisons with expert human play.

In Clarke, M. R. B. (Ed.), Advances in Computer Chess 2, pp. 103-109. Edinburgh University Press