Saul Amarel

Bio: Saul Amarel is an academic researcher. The author has contributed to research in topics: Adaptive reasoning & Intelligent decision support system. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

On representations and modeling in problem solving and on future directions for intelligent systems

Abstract: : The problem of representations in problem solving is introduced, and its significance for progress in machine intelligence is discussed. The related problem of forming and using models in machine problem solving is also discussed. Some current research in these areas is reviewed, and open problems are outlined. In addition, more general comments on the state of the art in artificial intelligence are made from the viewpoint of a designer of complex, computer-based, information processing systems. The question of establishing a conceptual framework for intelligent problem solving that would enable designers to generalize and transfer results from specific research projects in the area into their 'real life' situations receives special attention. (Author)

On Automated Scientific Theory Formation: A Case Study using the AM Program

Abstract: A program called "AM" is described which carries on simple mathematics research, defining and studying new concepts under the guidance of a large body of heuristic rules. The 250 heuristics communicate via an agenda mechanism, a global priority queue of small tasks for the program to perform, and reasons why each task is plausible (for example, "Find generalizations of 'primes', because 'primes' turned out to be so useful a concept"). Each concept is represented as an active, structured knowledge module. One hundred very incomplete modules are initially supplied, each one corresponding to an elementary set-theoretic concept (for example, union). This provides a definite but immense space which AM begins to explore. In one hour, AM rediscovers hundreds of common concepts (including singleton sets, natural numbers, arithmetic) and theorems (for example, unique factorization). As AM defines concepts, and fills in their facets, it does not synthesize new heuristics for dealing effectively with those new concepts. This inability turns out to be its main limitation.

A man-machine synergistic approach to planning and creative problem solving: Part II†

Abstract: This paper describes a proposed system, Gaku, as a step toward man-machine synergism. Characteristics of planning processes are described in terms of the levels of planning (conceptual, definitional, developmental, and operational) and the stages of problem solving (goal setting, alternative generation, consequence estimation, and evaluation and alternative selection). Structural attributes extracted from these characteristics constitute the basic framework and guiding mechanism for man's interaction with Gaku. An example of man-machine interaction is presented, suggesting desirable capabilities of Gaku. Features of Gaku are then described in terms of both built-in caPabilities that are relatively problem independent, and man-machine actions for dynamic extension of these capabilities that are problem dependent and user oriented. The latter can be seen to make the system increasingly useful and powerful as a “co-evolving” man-machine team.