PSY BEH 11B Lecture Notes - Lecture 10: Functional Fixedness, Hill Climbing, Maxima And Minima
10 Nov 2015
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Document Summary
Overview: well-defined problems, heuristics to search problem spaces. Insight vs. trial & error: expert problem solving, role of practice, talent. Views of problem solving: well-defined problems, much studied in ai, requires search, domain general heuristics for solving problems. Ill-defined problems: no real mechanisms for dealing with these, problem may be solved by suddenly seeing the problem differently, often requires developing a suitable representation. Problem solving as search: problem solving is a search problem, initial state- solution- goal state, search spaces can be large. If search space is too large : not possible to enumerate the entire search space for many well-defined problems, must use heuristics, not guaranteed to work, but easy to implement, example heuristics. Means-end analysis: set up a goal, look for a difference between current state and goal or subgoal state, find an operator to reduce this difference, setting a new subgoal, apply operator, repeat until final goal is achieved.
