Computational Approaches To Analogical Reasoning

Computational Approaches to Analogical Reasoning: Current Trends

Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity and dissimilarity indicators, and analogical proportions in lattice structures. Lastly, the volume reports case studies and discussions about the use of similarity judgments and the process of analogy making, at work in IQ tests, creativity or other cognitive tasks. This volume gathers fully revised and expanded versions of papers presented at an international workshop‚ as well as invited contributions. All chapters have benefited of a thorough peer review process.

Analogical Reasoning

The Analogical Mind

Analogy has been the focus of extensive research in cognitive science over the past two decades. Through analogy, novel situations and problems can be understood in terms of familiar ones. Indeed, a case can be made for analogical processing as the very core of cognition. This is the first book to span the full range of disciplines concerned with analogy. Its contributors represent cognitive, developmental, and comparative psychology; neuroscience; artificial intelligence; linguistics; and philosophy. The book is divided into three parts. The first part describes computational models of analogy as well as their relation to computational models of other cognitive processes. The second part addresses the role of analogy in a wide range of cognitive tasks, such as forming complex cognitive structures, conveying emotion, making decisions, and solving problems. The third part looks at the development of analogy in children and the possible use of analogy in nonhuman primates. Contributors Miriam Bassok, Consuelo B. Boronat, Brian Bowdle, Fintan Costello, Kevin Dunbar, Gilles Fauconnier, Kenneth D. Forbus, Dedre Gentner, Usha Goswami, Brett Gray, Graeme S. Halford, Douglas Hofstadter, Keith J. Holyoak, John E. Hummel, Mark T. Keane, Boicho N. Kokinov, Arthur B. Markman, C. Page Moreau, David L. Oden, Alexander A. Petrov, Steven Phillips, David Premack, Cameron Shelley, Paul Thagard, Roger K.R. Thompson, William H. Wilson, Phillip Wolff