Case-by-Case Problem Solving

Case-by-case Problem Solving solves each occurrence, or case, of a problem using available knowledge and resources on the case. It is different from the traditional Algorithmic Problem Solving, which applies the same algorithm to all occurrences of all problem instances. Case-by-case Problem Solving is suitable for situations where the system has no applicable algorithm for a problem. This approach gives the system flexibility, originality, and scalability, at the cost of predictability. This paper introduces the basic notion of Case-by-case Problem Solving, as well as its most recent implementation in NARS, an AGI project.

[1]  P. Veenhuis.  The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics , 1995 .

[2]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[3]  A. Newell.  Unified Theories of Cognition , 1990 .

[4]  Allen Newell,et al.  Computer science as empirical inquiry: symbols and search , 1976, CACM.

[5]  Pei Wang,et al.  Rigid Flexibility: The Logic of Intelligence , 2006 .

[6]  D. Hofstadter.  Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought, Douglas Hofstadter. 1994. Basic Books, New York, NY. 512 pages. ISBN: 0-465-05154-5. $30.00 , 1995 .

[7]  Pei Wang.  Problem-Solving under Insu cient Resources , 1995 .

[8]  Mark S. Boddy,et al.  An Analysis of Time-Dependent Planning , 1988, AAAI.

[9]  Martin D. Davis,et al.  Computability and Unsolvability , 1959, McGraw-Hill Series in Information Processing and Computers.

[10]  Pei Wang,et al.  Problem Solving With Insufficient Resources , 2005, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[11]  Pei Wang,et al.  Non-axiomatic reasoning system: exploring the essence of intelligence , 1996 .

[12]  David Leake,et al.  Case-Based Reasoning: Experiences, Lessons and Future Directions , 1996 .

[13]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[14]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[15]  R. K. Shyamasundar,et al.  Introduction to algorithms , 1996 .

[16]  R. Weale.  Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .

[17]  Pei Wang,et al.  Three fundamental misconceptions of Artificial Intelligence , 2007, J. Exp. Theor. Artif. Intell..

[18]  Stuart J. Russell,et al.  Principles of Metareasoning , 1989, Artif. Intell..