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Publication in BibTeX Format

@TECHREPORT{AICPub1079:1970, AUTHOR={Chaitin, L. J., Duda, R. O., Johanson, P. A., Raphael, B., Rosen, C. A. and Yates, R. A.}, TITLE={Research and Applications - Artificial Intelligence}, INSTITUTION={Stanford Research Institute}, MONTH={April}, YEAR={1970}, ABSTRACT={The primary objectives of this program are to investigate and develop techniques in artificial intelligence and apply them to the control of a mobile automaton, enabling it to carry out tasks, autonomously, in a realistic laboratory environment. As part of technique developments, there are reports of progress in scene analysis, and short-term and long-term problem solving. Scene analysis is aimed at providing the au tomaton system with its primary source of information about its environment. Such information (primarily visual) must be entered into appropriate internal models in a form useful for the problem-solving and planning systems. Several parallel approaches—line analysis and region analysis methods—are discussed, together with how knowledge of the actual environment is used to help interpret the processed information. The short-term problem-solving research is primarily aimed at providing new tools and concepts for coping with tasks of increased complexity to be implemented in the next year. A major software tool, QA3 (a question-answering system using theorem proving by resolution), will be revised and upgraded, permitting experimentation with new strategies and also allowing the theorem prover to be used in planning. Underway are implementations of a new n-tuple model and set of operators–routines that, when executed according to some plan, cause the robot to perform specific actions. Both primitive and more complex operators are being defined; these are callable in correct sequence by a planner. The planner organization is the subject of considerable research, which includes the possible use of a GPS-like deductive mechanism, perhaps together with the revised QA3 system. Finally, executive routines are being developed to supervise execution of operator sequences and updating of models, assessing cost-effectiveness of plans, making decisions such as regarding the need for new sensory information or abandonment of further planning in favor of execution, etc. The long-term problem-solving research is devoted to design and implementation of a general-purpose formal problem-solving system, QA4 based on mechanized theorem proving in higher-order logic. It is being designed to emphasize the role of semantic information processing and flexible control strategies. It will provide a rich language permitting syntax and semantics of any part of the system to be expressed in its own language, and will include set operations bridging logical and computational operations. It is expected to provide tools and techniques suitable for long-range research in such diverse fields as automatic program writing and robot planning. Appendices include:

}, NOTE={Project 8259 Interim Scientific Report.
From the Nilsson archives – SHAKEY papers} }

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