| Authors: |
Nick Chater
and Joshua B. Tenenbaum
and Alan Yuille
|
| URL: |
http://www.sciencedirect.com/science/article/B6VH9-4K8SC6G-2/2/a664cd85339f8b0642a9c43707701c40 |
| Description: |
ScienceDirect - Trends in Cognitive Sciences : Probabilistic models of cognition: Conceptual foundations |
| Tags: |
cognition
probabilistic
probability
|
| Abstract: |
Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, `sophisticated' probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore how the approach relates to studies of explicit probabilistic reasoning, and give a brief overview of the field as it stands today. |
@article{tics2006,
title = {Probabilistic models of cognition: Conceptual foundations},
author = {Nick Chater and Joshua B. Tenenbaum and Alan Yuille},
booktitle = {Special issue: Probabilistic models of cognition},
journal = {Trends in Cognitive Sciences},
month = {#jul#},
number = {7},
pages = {287--291},
url = {http://www.sciencedirect.com/science/article/B6VH9-4K8SC6G-2/2/a664cd85339f8b0642a9c43707701c40},
volume = {10},
year = {2006},
description = {ScienceDirect - Trends in Cognitive Sciences : Probabilistic models of cognition: Conceptual foundations},
abstract = {Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, `sophisticated' probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore how the approach relates to studies of explicit probabilistic reasoning, and give a brief overview of the field as it stands today.},
keywords = {cognition probabilistic probability }
}
::