Abstract
It is conjectured that a good cognitive psychology theory will lead to a good artificial intelligence (AI) program. If this is true there should be a convergence of psychological and AI considerations in theory construction. This convergence is illustrated in terms of ACT, a computer simulation model of cognitive processes. Separate AI and psychological considerations are used to motivate the decision to design ACT as a production system operating on an network data base. Similar motivation is provided for other features of ACT implemented within this framework. These features include the use of a propositional structure for the associative network, a spreading activation process operating on the network, the simulated ability to execute several procedures in parallel, and the use of strength measures to select among competing productions and competing paths in the network.We have been working on a production system model of human cognition called ACT. An earlier version of the ACT system, called ACTE, is described in Anderson [3], Anderson, Kline, and Lewis [5], and Kline and Anderson [2]. That system has been used to develop mini-models for retrieval from memory, inference making, language comprehension, question-answering, and problem solving. We are currently working on a new version of ACT called ACTF. This paper discusses a number of the design decisions underlying the ACT system. We will discuss how these design decisions are motivated by both psychological and artificial intelligence (AI) considerations.
- Aho, A. V., Hopcroft, J. E., & Ullman, J. D. The Design and Analysis of Computer Algorithms. Addison-Wesley, Reading, Mass., 1974. Google ScholarDigital Library
- Anderson, J. R. Language acquisition by computer and child. Technical Report No. 55, Human Performance Center, 1974.Google Scholar
- Anderson, J. R. Language, Memory, and Thought. Lawrence Erlbaum Associates, Hillsdale, N.J., 1976.Google Scholar
- Anderson, J. R. and Bower, G. H. Human Associative Memory. Winston, Washington, D.C., 1973.Google Scholar
- Anderson, J. R., Kline, P. and Lewis, C. A production system model for language processing. In Cognitive Processes in Comprehension, P. Carpenter and M. Just (Eds.) Lawrence Erlbaum Assoc., Hillsdale, N.J., in press.Google Scholar
- Anderson, R. C. Substance recall of sentences. Quarterly Journal of Experimental Psychology, 26, 1974, 530--541.Google ScholarCross Ref
- Baddeley, A. D. and Hitch, G. Working memory. In The Psychology of Learning and Motivation, 8, G. H. Bower (Ed.) Academic Press, New York, 1974.Google Scholar
- Bever, T. G., Fodor, J. A., and Garrett, M. A formal limitation of associationism. In T. R. Dixon and D. L. Horton (Eds.) Verbal Behavior and General Behavior Theory. Prentice-Hall, Englewood Cliffs, N.J., 1968.Google Scholar
- Chase, W. G. and Simon, H. A. The mind's eye in chess. In Chase (Ed.), Visual Information Processing, Chase, W. G. (Ed.), Academic Press, New York, 1973.Google Scholar
- Chomsky, N. Verbal behavior (a review of Skinner's book). Language, 35, 1959, 26--58.Google ScholarCross Ref
- Collins, A. M. & Loftus, E. F. A spreading-activation theory of semantic processing. Psychological Review, 82, 1975, 407--428.Google ScholarCross Ref
- Collins, A. M. & Quillian, M. R. Experiments on semantic memory and language comprehension. In Cognition and Learning, Gregg, L. (Ed.), Wiley, New York, 1972.Google Scholar
- Crowder, R. G. Behavioral strategies in immediate memory. Journal of Verbal Learning and Verbal Behavior, 8, 1969, 524--528.Google ScholarCross Ref
- Davis, R. and King, J. An overview of production systems. Computer Science Department, Stanford University, 1975.Google ScholarCross Ref
- Fodor, J. A., Bever, T. G., and Garrett, M. F. The Psychology of Language. McGraw-Hill, New York, 1974.Google Scholar
- Fredericksen, C. Effects of context-induced processing operations on semantic information acquired from discourse. Cognitive Psychology, 7, 1975, 139--166.Google ScholarCross Ref
- Johnson, D. M. A Systematic Introduction to the Psychology of Thinking. Harper and Row, New York, 1972.Google Scholar
- Kieras, D. E. Finite automata and S-R models. Journal of Mathematical Psychology, 3, 1976, in press.Google Scholar
- Kieras, D. E. Problems of reference in text comprehension. In Cognitive Processes in Comprehension. Carpenter, P. and Just, M. (Eds.) Lawrence Erlbaum Assoc., Hillsdale, N.J., in press.Google Scholar
- Kiss, G. R. A test of the word selection model using multiple stimuli in word association. Paper presented at the conference of the British Psychological Society, London, 1967.Google Scholar
- Kline, P. and Anderson, J. R. The ACTE User's Manual. Dept. of Psychology, Yale University, 1976.Google Scholar
- McDermott, J., Newell, A., and Moore, J. The efficiency of certain production system implementations. Dept. of Computer Science, Carnegie Mellon University, Sept., 1976.Google Scholar
- Meyer, D. E. & Schvaneveldt, R. W. Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 1971, 27--234.Google ScholarCross Ref
- Minsky, M. Semantic Information Processing. The M.I.T. Press, Cambridge, 1968. Google ScholarDigital Library
- Newell, A. Remarks on the relationship between artificial intelligence and cognitive psychology. In Theoretical Approaches to Non-Numerical Problem Solving, R. B. Banerji and M.D. Mesarovic (Eds.), Springer-Verlag, Berlin, 1970.Google ScholarCross Ref
- Newell, A. and Simon, H. Human Problem Solving. Prentice-Hall, Englewood Cliffs, N.J., 1972. Google ScholarDigital Library
- Quillian, M. R. Semantic memory. In M. Minsky (Ed.) Semantic Information Processing, MIT Press, Cambridge, 1968.Google Scholar
- Sachs, J. Recognition memory for syntactic and semantic aspects of connected discourse. Perception and Psychophysics, 2, 1967, 437--442.Google ScholarCross Ref
- Thompson, R. F. Foundations of Physiological Psychology, Harper & Row, New York, 1967.Google Scholar
- Savin, H. B. and Perchonock, E. Grammatical structure and the immediate recall of English sentences. Journal of Verbal Learning and Verbal Behavior, 4, 1965, 348--353.Google ScholarCross Ref
- Simon, H. A. The Sciences of the Artificial. MIT Press, Cambridge, 1969. Google ScholarDigital Library
- Wanner, H. E. On remembering, forgetting, and understanding sentences: A study of the deep structure hypothesis. Unpublished doctoral dissertation, Harvard University, 1968.Google Scholar
- Wanner, E. and Maratsos, M. An augmented transition network model of relative clause comprehension, unpublished manuscript, Harvard University, 1975.Google Scholar
- Winograd, T. Procedures as a representation for data in a computer program for understanding natural language. MIT Artificial Intelligence Laboratory Project, MAC-TR-84, 1971.Google Scholar
- Woods, W. A. What's in a link: Foundations for semantic networks. In Representation and Understanding: Studies in Cognitive Science, Bobrow, D. G. and Collins, A. (Eds.), Academic Press, New York, 1975.Google Scholar
Index Terms
- Design of a production system for cognitive modeling
Recommendations
Modeling of agile intelligent manufacturing-oriented production scheduling system
Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed ...
Towards the Synergy of Cognitive Informatics, Neural Informatics, Brain Informatics, and Cognitive Computing
The contemporary wonder of sciences and engineering recently refocused on the starting point: how the brain processes internal and external information autonomously rather than imperatively as those of conventional computers? This paper explores the ...
Contemporary cybernetics and its facets of cognitive informatics and computational intelligence
Special issue on cybernetics and cognitive informaticsThis paper explores the architecture, theoretical foundations, and paradigms of contemporary cybernetics from perspectives of cognitive informatics (CI) and computational intelligence. The modern domain and the hierarchical behavioral model of ...
Comments