Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Deconstructing analogy (1308.2119v1)

Published 9 Aug 2013 in cs.AI

Abstract: Analogy has been shown to be important in many key cognitive abilities, including learning, problem solving, creativity and language change. For cognitive models of analogy, the fundamental computational question is how its inherent complexity (its NP-hardness) is solved by the human cognitive system. Indeed, different models of analogical processing can be categorized by the simplification strategies they adopt to make this computational problem more tractable. In this paper, I deconstruct several of these models in terms of the simplification-strategies they use; a deconstruction that provides some interesting perspectives on the relative differences between them. Later, I consider whether any of these computational simplifications reflect the actual strategies used by people and sketch a new cognitive model that tries to present a closer fit to the psychological evidence.

Citations (1)

Summary

We haven't generated a summary for this paper yet.