Skip to main content
Article thumbnail
Location of Repository

Combining weak learning heuristics in general problem solvers

By T.L. McCluskey


This paper is concerned with state space problem\ud solvers that achieve generality by learning strong\ud heuristics through experience in a particular domain. We specifically consider two ways of learning by analysing past solutions that can improve future problem solving: creating macros and the chunks. A method of learning search heuristics is specified which is related to 'chunking' but which complements the use\ud of macros within a goal directed system. An example of the creation and combined use of macros and chunks, taken from an implemented system, is described

Topics: Q1, T1
Year: 1987
OAI identifier:

Suggested articles


  1. (1977). and S i k lossy , L. "The Role of Preprocessing in Problem Solving Systems".
  2. (1984). Careful Generalisation for Concept Learning",
  3. (1986). Chunking in Soar: The Anatomy of a General Learn ing Mechanism" doi
  4. (1986). Explanation-Based Genralisation: A Unifying View"
  5. (1977). Induction of Relational Productions in the Presence of Background Information",
  6. (1972). Learning and Executing General ised Robot Plans", Ar t i f ic ia l doi
  7. (1985). Learning by Discovering Macros in Puzzle Solving".
  8. (1983). Learning by Experimentation: Acquiring and Refining Problem Solving Heuristics", doi
  9. (1984). Learning Operator Transformations",
  10. (1985). Learning to Search: From Weak Methods to Domain-Specific Heuristics", doi
  11. (1985). Macro Operators: A Weak Method for Learning", doi
  12. (1985). Selectively Generalising Plans for Problem Solving",
  13. (1984). Toward Chunking as a General Learning Mechanism", doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.