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Carruthers, Sarah; Masson, Michael E. J.; Stege, Ulrike – Journal of Problem Solving, 2012
Recent studies on a computationally hard visual optimization problem, the Traveling Salesperson Problem (TSP), indicate that humans are capable of finding close to optimal solutions in near-linear time. The current study is a preliminary step in investigating human performance on another hard problem, the Minimum Vertex Cover Problem, in which…
Descriptors: Performance, Problem Solving, Graphs, Mathematics
Ginat, David – Journal of Computers in Mathematics and Science Teaching, 2005
Sometimes, if you do not begin at the end, you end at the beginning. This problem-solving phenomenon, in the realm of computer science (CS), is the subject of this paper. Beginning at the end yields a "working backwards" approach, opposite to that of "working forwards." One might expect 3rd year CS students to be aware of and effectively utilize…
Descriptors: Computer Science, Problem Solving, Heuristics, Preservice Teachers
Clancey, William J. – 1984
In an attempt to specify in some canonical terms what many heuristic programs known as "expert systems" do, an analysis was made of ten rule-based systems. It was found that these programs proceed through easily identifiable phases of data abstraction, heuristic mapping onto a hierarchy of pre-enumerated solutions, and refinement within this…
Descriptors: Classification, Computer Science, Computer Software, Heuristics

Schell, George P. – Journal of Educational Technology Systems, 1988
Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)
Descriptors: Algorithms, Artificial Intelligence, Computer Science, Heuristics

Waldrop, M. Mitchell – Science, 1988
Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Cognitive Structures
Psotka, Joseph – 1985
Current notions of metacognition merge with the predominant scientific model used in psychology, that of information processing. Metacognition is seen as a control process that governs the action of more elemental cognitive skills. Given the centrality of this notion, it is important that metacognition should be examined in detail. From the point…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Restructuring, Computer Assisted Instruction
Clancey, William J. – 1985
A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…
Descriptors: Artificial Intelligence, Classification, Computer Oriented Programs, Computer Science

Waldrop, M. Mitchell – Science, 1988
Traces the history and function of State, Operator, And Result (SOAR), a general-purpose artificial intelligence program for solving problems. The SOAR can "chunk" the result of a subgoal and learn from previous experiences. The SOAR could be applied to various expert systems. (YP)
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, College Science