Technology
On Automated Scientific Theory Formation: A Case Study using the AM Program
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.
AGE: A knowledge-based program for building knowledge-based programs
The goal of the ACE project is to demystify and make explicit the art of knowledge engineering. It is an attempt to formulate the knowledge that knowledge engineers use in constructing knowledge-based programs and put it at the disposal of others in the form of a software laboratory. To achieve this goal, the task for ACE is divided into two main sub-tasks: (1) isolating techniques used in knowledge-based systems and programming those that are general and useful (2) building an intelligent agent to guide in the use of these techniques.
The interaction of observation and inference in a formal representation system
This work is an attempt to formally represent the knowledge required for the solution of a difficult retrograde chess problem (figure I). This solution Includes the extension of a formal deductive system to Include an observational facility. FOL [9], we have detailed a proof of the solution of the puzzle, Including proofs for almost all of the necessary associated lemmas [2], We shall highlight the various representational decisions made In the process of axiomatiiing retrograde chess, discussing both the necessity for these particular choices, and their Implications for designers of representations for other domains. This work is part of the search for epistemologically effective formalisms for artificial Intelligence.