Computational models of analogy

Abstract

Analogical mapping is a core process in human cognition. A number of valuable computational models of analogy have been created, capturing aspects of how people compare representations, retrieve potential analogs from memory, and learn from the results. In the past 25 years, this area has progressed rapidly, fueled by strong collaboration between psychologists and Artificial Intelligence (AI) scientists, with contributions from linguists and philosophers as well. There is now considerable consensus regarding the constraints governing the mapping process. However, computational models still differ in their focus, with some aimed at capturing the range of analogical phenomena at the cognitive level and others aimed at modeling how analogical processes might be implemented in neural systems. Some recent work has focused on modeling interactions between analogy and other processes, and on modeling analogy as a part of larger cognitive systems. WIREs Cogni Sci 2011 2 266–276 DOI: 10.1002/wcs.105 This article is categorized under: Computer Science > Artificial Intelligence Psychology > Reasoning and Decision Making