Abstract
In this chapter we describe Eureka, a problem solver that uses analogy as its basic reasoning and learning process. Eureka introduces a learning mechanism called analogical search control, and uses a model of memory based on spreading activation to retrieve analogies and solve problems. These relatively simple mechanisms allow the system to account for a number of psychological phenomena in problem solving. In this chapter we focus on some of the computational aspects of the system. To this end, we provide a full description at theoretical and implementation levels, and present the results of some experiments that explore the model’s computational behavior.
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Jones, R. (1993). Problem Solving via Analogical Retrieval and Analogical Search Control. In: Meyrowitz, A.L., Chipman, S. (eds) Foundations of Knowledge Acquisition. The Springer International Series in Engineering and Computer Science, vol 195. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-27366-2_7
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DOI: https://doi.org/10.1007/978-0-585-27366-2_7
Publisher Name: Springer, Boston, MA
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