This paper is a preliminary proposal to develop the theory and design for "coaches" for computer games, to implement prototypes, and to experiment with their ability to convey important intellectual skills. The focus of this project will be restricted to developing a coach for a single example of an intellectual game called Wumpus. It is pointed out that, while computer games have a powerful educational appeal, they also have a limitation in that the player, on his own, can fail to acquire the skills of an expert. A computer coach, which could provide advice on strategy and tactics for better play and tutor basic mathematical, scientific, or other kinds of knowledge related to the game, could overcome that limitation. The project would address three specific questions: (1) how the expertise can be designed in the coach so that it can respond reasonably to the player's particular choice of move; (2) how the player can be modeled sufficiently so that the coach's remarks are appropriate, i.e., neither too advanced for a beginner nor too elementary for an expert; and (3) how the nature of the coach's advice can be controlled so that it is given in a friendly and personal manner.

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The program analyses carefully the initial situation. It creates some plans and tries to execute them. It analyses the situations deeper in the tree only if the plan fails. In that case it generates new plans correcting what is wrong in the old one. So, the program considers only natural branches of the tree. It can find combinations for which it is necessary to look more than twenty ply ahead. The paper describes the methods used for analyzing a situation and for modifying unsuccessful plans. Then we examine some results found by the program.Artificial Intelligence 8 (1977), 275-321

See also: Stanford Heuristic Programming Project Memo HPP-77-25Proc. IJCAI-77: Fifth International Joint Conference on Artificial Intelligence, pp 1014-1029

Austin Tate Department of Artificial Intelligence University of Edinburgh Edinburgh Scotland Abstract Procedures for optimization and resource allocation in Operations Research first require a project network for the task to be specified. The specification of a project network is at present done in an intuitive way. AI work in plan formation has developed formalisms for specifying primitive activities, and recent work by Sacerdoti (1975a) has developed a planner able to generate a plan as a partially ordered network of actions. The "planning: a joint AI/OR approach" project at Edinburgh has extended such work and provided a hierarchic planner which can aid in the generation of project networks. This paper describes the planner (NONLIN) and the Task Formalism (TF) used to hierarchically specify a domain. Current work in Operations Research (OR) and Artificial Intelligence (AI) has concentrated on different aspects of the problem. We have taken an interdisciplinary approach in the hope that this will lead to a development of both these aspects. In the OR approach, the planning process falls into two stages. The constituent "jobs" of a plan are specified together with their precedence relationships (i.e.

Book-length version of the central ideas presented in Roger C. Schank and Robert P. Abelson, "SCRIPTS, PLANS, AND KNOWLEDGE" http://oak.conncoll.edu/parker/com316/progassign/scripts.pdf Hillsdale, NJ: Lawrence Erlbaum Associates

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This paper is concerned primarily with (1) the procedure by which process-oriented specifications are obtained from goal-oriented requirement specifications and (2) computer-based tools for their construction. It first determines some attributes of a suitable process-oriented specification language, then examines the reasons why specifications would still be difficult to write in such a language. The key to overcoming these difficulties seems to be the careful introduction of informality based on partial, rather than complete, descriptions and the use of a computer-based tool that uses context extensively to complete these descriptions during the process of constructing a well-formed specification. Some results obtained by a running prototype of such a computer-based tool on a few informal example specifications are presented and, finally, some of the techniques used by this phototype system are discussed.

Such features include spelling correction, processing of incomplete (ell ipt ic-I) input?, jntfrrog-t ior of th