|Speaker||Noah D. Goodman|
|Affiliation||Assistant Professor of Psychology, Stanford University|
|Date and Time||Sept. 3, 2013, 4 p.m. - 05:00 p.m.|
|Location||Singleton Auditorium, MIT Bldg 46-3002|
MIT Intelligence Initiative Seminar Series
presents Noah D. Goodman, Stanford University
Abstract: Human reasoning is a beautiful puzzle: it is productive, extending to new situations without bound, and it is uncertain, dealing gracefully with noisy evidence and shades of belief. Reasoning is also a key window on cognition, providing some of our best evidence about the structures that underly everyday, commonsense thought. I will argue that the core representations that support reasoning can be understood as a 'probabilistic language of thought', and that reasoning is an approximation to probabilistic inference. I will illustrate this claim with examples of reasoning about games and property induction. However, I will suggest that the bridge between the probabilistic language of thought and empirical data is a firm understanding of natural language. I will sketch a model of natural language pragmatics and semantics, and describe experimental evidence from communication games and quantity implicature. I will then describe how we can extend this framework to encompass vague language, focussing on scalar adjectives (like "tall"). I will conclude by coming back to reasoning, explaining two puzzling patterns: the sorites paradox and the effect of additional premises when reasoning general-to-specific. Time permitting, I will discuss possible process-level implementations in a short coda.
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