Retrieval and Learning in Analogical Problem Solving
Randolph M. Jones, Pat Langley · 2007
EUREKA is a problem-solving system that operates through a form of analogical reasoning. The system was designed to study how relatively low-level memory, reasoning, and learning mechanisms can account for high-level learning in human problem solvers. Thus, EUREKA's design has focused on issues of memory representation and retrieval of analogies, at the expense of complex problem-solving ability or sophisticated analogical elaboration techniques. Two computational systems for analogical reasoning, ARCS/ACME and MAC/FAC, are relatively powerful and well-known in the cognitive science literature. However, they have not addressed issues of learning, and they have not been implemented in the context of a performance task that can dictate what makes an analogy "good". Thus, it appears that these different research directions have much to offer each other. We describe the EUREKA system and compare its analogical retrieval mechanism with those in ARCS and MAC/FAC. We then discuss the issues i...