ТОП 10:

Linster M. and Musen M. A. (1992). Use of KADS to create a conceptual model of the

ONCOCINtask. Knowledge Acquisition, 4, p. 55-87. MacGregor R. (1991). Inside the LOOM classifier. SIGART Bulletin, 2(3), p. 70-76.

Mamdani E. H. and Gaines B. R. (1981). Fuzzy Reasoning and its Applications. London: Academic Press.

Marcus S., eds. (1988, a). Automating Knowledge Acquisition for Expert Systems. Boston: Kluiver Academic.

Marcus S. (1988, b). A knowledge acquisition tool for propose-and-revise systems. In Automating Knowledge Acquisition for Expert Systems (Marcus S., eds.). Chapter 4. Boston: Kluiver Academic.

Marcus S., Stout J. and McDermott J. (1988). VT: an expert elevator configurer that uses knowledge-based backtracking. AI Magazine, 9(1), p. 95-112.

Marir F. and Watson I. (1994). Case-based reasoning: a categorized bibliography. Knowledge

Engineering Review, 9(4), p. 355-381. Martins J. P. and Reinfrank M. (1991). Truth Maintenance Systems. Lecture Notes in Artificial

Intelligence, No. 515. Berlin: Springer Verlag. Maybury M., eds. (1993). Intelligent Multi-Media Interfaces. Cambridge, MA: AAAI

Press/MIT Press.

McAllester D. (1980). An Outlook on Truth Maintenance. Report No. AIM-551, Artificial Intelligence Laboratory, Massachusetts Institute of Technology.

McArthur D., Klahr P. and Narain S. (1986). ROSS: an object-oriented language for constructing simulations. In Expert Systems: Techniques, Tools and Applications (Klahr P. and Waterman D., eds.). Chapter 3. Reading, MA: Addison-Wesley.

McCarthy J. (1960). Recursive functions of symbolic expressions and their computation by machine. Communications of the Association for Computing Machinery, April, p, 184-195. McCarthy J. and Hayes P. (1969). Some philosophical problems from the standpoint of artificial intelligence. In Machine Intelligence 4 (Meltzer B. and Michie D., eds.), p. 463-502. Edinburgh: Edinburgh University Press.

McCarthy J., Abrahams P. W., Edwards D. I., Hart T. P. and Levin M. I. (1965). LISP 1.5 Programmer's Manual, 2nd edn. Cambridge, MA: MIT Press.

McDermott J. (1980). Rl: an expert in the computer system domain. In Proc. National Conference on Artificial Intelligence, p. 269-271. McDermott J. (1981). Rl's formative years. AIMagazine, 2(2).

McDermott J. (1982, a). Rl: a rule-based configurer of computer systems. Artificial Intelligence, 19, p. 39-88. McDermott J. (1982, b). XSEL: a computer sales person's assistant. In Machine Intelligence JO

(Hayes J. E., Michie D. and Pao Y. H., eds.), p. 325-337. Chichester, UK: Ellis Horwood. McDermott J. (1984). Building expert systems. In Artificial Intelligence Applications for Business (Reitman W., eds.). Norwood, NJ: Ablex.

McDermott J. (1988). Preliminary steps towards a taxonomy of problem solving methods. In Automating Knowledge Acquisition for Expert Systems (Marcus S., eds.), Chapter 8. Boston: Kluiver Academic. McDermott J. (1993). Rl ("XCON") at age 12: lessons from an elementary school achiever.

Artificial Intelligence, 59, p. 241-247. McDermott J. and Bachant J. (1984). Rl revisited: four years in the trenches. AI Magazine,

Fall, p. 21-32.

McDermott J. and Forgy C. L. (1978). Production system conflict resolution strategies. In Pattern Directed Inference Systems (Waterman D. A. and Hayes-Roth F., eds.), p. 177-199. New York: Academic Press.

McNeill D. and Freiberger P. (1993). Fuzzy Logic. New York: Simon and Schuster. Meltzer B. and Michie D., eds. (1969). Machine Intelligence 4. Edinburgh: Edinburgh University Press.

Meyers S. (1995). More Effective C++ : 35 New Ways to Improve Your Programs and Designs. Reading, MA: Addison-Wesley.

Meyers S. (1997). Effective C++ ; 50 Specific Ways to Improve Vom Programs and Designs, 2nd edn. Reading, MA: Addison-Wesley.

Michalski R. S. (1983). A theory and methodology of inductive learning. In Machine Learning (Michalski R. S., Carbonell J. G. and Mitchell T. M., eds.), Chapter 4. Palo Alto, CA: Tioga.

Michalski R. S., Carbonell J. G. and Mitchell T. M., eds. (1983). Machine Learning. Palo Alto, CA: Tioga.

Michalski R. S., Carbonell J. G. and Mitchell T. M, eds. (1986). Machine Learning Vol. II. Palo Alto, CA: Tioga.

Michie D., eds. (1968). Machine Intelligence 3. Edinburgh: Edinburgh University Press.

Michie D., eds. (1979). Expert Systems in the Micro-Electronic Age. Edinburgh: Edinburgh University Press.

Mingers J. (1989, a). An empirical comparison of selection measures for decision tree induction. Machine Learning, 3, p. 319-342.

Mingers J. (1989, b). An empirical comparison of pruning methods for decision tree induction. Machine Learning, 4, p. 227-243.

Minsky M., eds. (1968). Semantic Information Processing. Cambridge, MA: MIT Press. Minsky M. (1972). Computation: Finite and Infinite Machines. London: Prentice-Hall.

Minsky M. (1975). A framework for representing knowledge. In The Psychology of Computer Vision (Winston P. H., eds.) p. 211-277. New York: McGraw-Hill. (Русский перевод: Минский М. Структура для представления знания. — В сб. Психология машинного зрения. Под. ред. П. Уинстона. М.: Мир, 1978. — с. 249-338.)

Mitchell Т. М. (1978). Version Spaces: An Approach to Concept Learning. Report No. STAN-CS-78-711, Computer Science Department, Stanford University.

Mitchell Т. М. (1982). Generalization as search. Artificial Intelligence, 18, 203-226.

Mitchell Т. М. (1997). Machine Learning. New York, NY: McGraw-Hill.

Mitchell T. M., Keller R. M. and Kedar-Cabelli S. T. (1986). Explanation-based generalization:

A unifying view. Machine Learning, 1(1), p. 47-80. Moore J. D. (1995). Participating in Explanatory Dialogues. Cambridge MA: MIT Press.

Moser M. G. (1983). An Overview of NIKL, the New Implementation of KL-ONE. Technical Report No. 5421, Cambridge MA: Bolt, Beranek and Newman.

Moore J. D. and Paris C. L. (1993). Planning text for advisory dialogues: capturing intentional and rhetorical information. Computational Linguistics, 19(4), p. 651-695.

Moore J. D., Lemaire B. and Rosenblum J. A. (1996). Discourse generation for instructional applications: identifying and exploiting relevant prior explanations. Journal of the Learning Sciences, 5(1), p. 49-94.

Musen M. A. (1992). Overcoming the limitations of role-limiting methods. Knowledge Acquisition, 4(2), p. 165-170.

Musen M. A. (1989). Automated support for building and extending expert models. Machine Learning, 4(3-4), p. 347-376.

Musen M. A., Gennari J. H. and Wong W. W. (1995). A rational reconstruction of INTERNIST-I using PROTEGE-II. Knowledge Systems Laboratory, Medical Computer Science, KSL-95-46.

Neale I. M. (1988). First generation expert systems: a review of knowledge acquisition methodologies. Knowledge Engineering Review, 3(2), p. 105-145.

Neapolitan R. E. (1990). Probabilistic Reasoning in Expert Systems: Theory and Algorithms. New York: Wiley.

Neches R., Swartout W. R. and Moore J. (1985). Explainable (and maintainable) expert systems. In Proc. 9th International Joint Conference on Artificial Intelligence, p. 382-389.

Newell A. (1981). Physical symbol systems. In Perspectives on Cognitive Science (Norman D. A., eds.), Chapter 4. Norwood, NJ: Ablex.

Newell A. (1982). The knowledge level. Artificial Intelligence, 18, p. 87-127. Newell A. and Simon H. A. (1972). Human Problem Solving. Englewood-Cliffs, NJ: Prentice-Hall.

Newell A. and Simon H. A. (1976). Computer science as empirical enquiry. Communications of the Association for Computing Machinery, 19(3), p. 113-126.

Nguyen Т., Czerwinski M. and Lee D. (1993). Compaq QuickSource: Providing the consumer with the power of artificial intelligence. In Innovative Applications of Artificial Intelligence 5, Proceedings ofAAAI-93, p. 142-151. Menlo Park, CA:. AAAI Press.

Nii H. P. (1986, a). Blackboard systems (Part 1). AIMagazine, 7(2), p. 38-53. Nii H. P. (1986, b). Blackboard systems (Part 2). Al Magazine, 7(3), p. 82-106.

Nii H. P. and Aiello N. (1979). AGE (Attempt to GEneralize): a knowledge-based program for building knowledge-based programs. In Proc. 6th International Joint Conference on Artificial Intelligence, p. 645-655.

Nii H. P., Aiello N. and Rice J. (1988). Frameworks for concurrent problem solving: a report on CAGE and POLIGON. In Blackboard Systems (Englemore R. and Morgan T, eds.), Chapter 25. Reading, MA: Addison-Wesley.

Nilsson N. J. (1971). Problem Solving Methods in Artificial Intelligence. New York: McGraw-Hill. (Русский перевод: НильсонН. Искусственный интеллект. Методы поиска решений. — М.: Мир, 1973. — 265 с.)

Nilsson N. J. (1980). Principles of Artificial Intelligence. Palo Alto, CA: Tioga. (Русский перевод: НильсонН. Принципы искусственного интеллекта.— М.: Радио и связь, 1985. —376с.)

Norman D. A., eds. (1981). Perspectives on Cognitive Science. Norwood NJ: Ablex.

Norvig P. (1992). Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp. Los Altos, CA: Morgan Kaufrnann.

O'Rourke P. (1982). A Comparative Study of Two Inductive Learning Systems AQ11 and ID3 Using a Chess Endgame Test Problem. Report No. 82-2, Department of Computer Science, University of Illinois.

O'Shea T. and Eisenstadt M., eds. (1984). Artificial Intelligence: Tools, Techniques, and Applications. New York: Harper and Row.

Paterson A. and Niblett T. (1982). ACLS Manual, Version 1. Glasgow, UK: Intelligent Terminals.

Pearl J. (1982). Reverend Bayes on inference engines: a distributed hierarchical approach. In Proc. National Conference on Artificial Intelligence, p. 133-136.

Pearl J. (1984). Heuristics. Intelligent Search Strategies for Computer Problem-Solving. Reading, MA: Addison-Wesley.

Pearl J. (1986). On evidential reasoning in a hierarchy of hypotheses. Artificial Intelligence, 28, p. 9-15.

Pearl J. (1988). Probabilistic Reasoning for Intelligent Systems. Los Altos, CA: Morgan Kauf-mann.

Pearl J. (1997). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Los Altos, CA: Morgan Kauftnann.

Pepper J. and Kahn G. (1987). Repair strategies in a diagnostic expert system. In Proc. 10th International Joint Conference on Artificial Intelligence, p. 531-534.

Peterson G. E., eds. (1987). Object-oriented computing, Vols 1 and 2. Washington DC: The Computer Society Press of the IEEE.

Poeson M. C. and Richardson J. (1988). Foundations of Intelligent Tutoring Systems. Hillsdale, NJ: Lawrence Erlbaum.

Pople H. E. Jr. (1977). The formation of composite hypotheses in diagnostic problem solving: an exercise in synthetic reasoning. In Proc. 5th International Joint Conference on Artificial Intelligence, p. 1030-1037.

Pople H. E. Jr. (1982). Heuristic methods for imposing structure on ill-structured problems: the structuring of medical diagnosis. In Artificial Intelligence in Medicine (Szolovits P., eds.), p. 119-190. Boulder, Co: Westview Cress.

Post E. L. (1943). Formal reductions of the general combinatorial decision problem. American

Journal of Mathematics, 65, p. 197-268. Poundstone W. (1988). Labyrinths of Reason. New York: Doubleday.

Prerau D. S. (1990). Developing and Managing Expert Systems. Reading, MA: Addison-Wesley.

Provan G. M. (1990). The application of Dempster-Shafer theory to a logic-based visual recognition system. In Uncertainty in Artificial Intelligence (Henrion M., Shachter R. D., Ka-nal L. N. and Lemmer J. E., eds.), p. 389^405. Amsterdam: North Holland.

Puerta A. R., Neches R., Eriksson H., Szeleky P., Luo P. and Musen M. A. (1994). Toward ontology-based frameworks for knowledge acquisition tools. In Proc. 8th Banff Knowledge-Based Systems Workshop, 26, p. 1-14.

Quillian M. R. (1968). Semantic memory. In Semantic Information Processing (Minsky M., eds.), p. 227-270. Cambridge, MA: MIT Press.

Quine W. V. O. (1979). Methods of Logic. London: Routledge Kegan Paul.

Quinlan J. R. (1979). Discovering rules from large collections of examples: a case study. In Expert Systems in the Micro-Electronic Age (Michie D., eds.), p. 168-201. Edinburgh: Edinburgh University Press.

Quinlan J. R. (1983). Learning efficient classification procedures and their application to chess endgames. In Machine Learning (Michalski A. S., Carbonell J. G. and Mitchell Т. М, eds.). Chapter 15. Palo Alto, С A: Tioga.

Quinlan J. R. (1986, a). Induction of decision trees. Machine Learning, 1, p. 81-106.

Quinlan J. R. (1986, b). The effect of noise on concept learning. In Machine Learning Vol. II (Michalski R. S., Carbonell J. G. and Mitchell T. M., eds.). Chapter 6. Palo Alto, CA: Tioga.

Quinlan J. R., eds. (1987). Applications of Expert Systems. Sydney: Addison-Wesley.

Quinlan J. R, (1993). C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kauf-mann.

Raphael B. (1976). The Thinking Computer: Mind inside Matter. San Francisco: W. H. Freeman.

Rayward-Smith V. J. (1994). Applications of Modern Heuristic Methods. Alfred Waller.

Rayward-Smith V. J., Osman I. H. and Reeves C. R., eds. (1996). Modern Heuristic Search Methods. New York: Wiley.

Reichgelt H. and van Harmelen E. (1986). Criteria for choosing representation languages and control regimes for expert systems. Knowledge Engineering Review, 1(4), p. 2-17.

Reitman W., eds. (1984). Artificial Intelligence Applications for Business. Norwood, NJ: Ablex.

Reynolds D. (1988). MUSE: a toolkit for embedded, real-time, AI. In Blackboard Systems (Englemore R. and Morgan Т., eds.), Chapter 27. Reading, MA: Addison-Wesley.

Rice J. (1986). POLIGON: A System for Parallel Problem Solving. Technical Report No. KSL-86-19, Knowledge Systems Laboratory, Stanford University.

Rice J. (1989). The advanced architectures project. AI Magazine, 10(4), p. 26-39. Rich E. and Knight K. (1991). Artificial Intelligence. New York: McGraw-Hill.

Richer M. H. and Clancey W. J. (1985). A graphic interface for viewing a knowledge based system. IEEE Computer Graphics and Applications, 5(11), p. 51-64.

Rine D. C., eds. (1975). Computer Science and Multiple-Valued Logic Theory and Applications. Amsterdam: North-Holland.

Rissland E. L., Daniels J. J., Rubinstein Z. B. and Skalak D. B. (1993). Case-based diagnostic analysis in a blackboard architecture. In Proc. llth National Conference on Artificial Intelligence, p. 66-72.

Robinson J. A. (1965). A machine-oriented logic based on the resolution principle. Journal of the Association for Computing Machinery, 12, p. 23-41. (Русский перевод: Робинсон Дж. Машинно-ориентированная логика, основанная на принципе резолюции. — В кн. Кибернетический сборник, вып. 7, 1970, — с. 194-218.)

Robinson J. A. (1979). Logic: Form and Function. Edinburgh: Edinburgh University Press.

Robinson V., Hardy N. W, Barnes D. P., Pace C. J. and Lee M. H. (1987). Experiences with a knowledge engineering toolkit: an assessment in industrial robotics. Knowledge Engineering Review, 2(1), p. 43-54.

Rose D. E. (1994). A Symbolic and Connectionist Approach to Legal Information Retrieval. Hillsdale, NJ: Lawrence Erlbaum.

Rosenman M. A., Coyne R. D. and Gero I. S. (1987). Expert systems for design applications. In Applications of Expert Systems (Quinlan J. R., eds.). Chapter 4. Sydney: Addison-Wesley.

Rothenfluh T. E., Gennari J. H., Eriksson H., Puerto A. R., Tu S. W. and MusenM. A. (1994). Reusable ontologies, knowledge acquisition tools, and performance systems: PROTOGE-II solutions to Sisyphus-2. In Proc. 8th Banff Knowledge-Based Systems Workshop, 43, p. 1-30.

Rumelhart D. E. (1988). Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Cambridge, MA: MIT Press.

Rumelhart D. E. and McClelland J. L. (1986) Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations. Cambridge, MA: MIT Press.

Russell S. J. and Norvig P. (1995). Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice-Hall.

Sacerdoti E. D. (1974). A Structure for Plans and Behavior. Amsterdam: Elsevier North-Holland.

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