A Comparative Approach to Understanding General Intelligence: Predicting Cognitive Performance in an Open-ended Dynamic Task

DOI

10.2991/agi.2009.2How to use a DOI?

Abstract

The evaluation of an AGI system can take many forms. There is a long tradition in Artificial Intelligence (AI) of competitions focused on key challenges. A similar, but less celebrated trend has emerged in computational cognitive modeling, that of model comparison. As with AI competitions, model comparisons invite the development of different computational cognitive models on a well-defined task. However, unlike AI where the goal is to provide the maximum level of functionality up to and exceeding human capabilities, the goal of model comparisons is to simulate human performance. Usually, goodness-of-fit measures are calculated for the various models. Also unlike AI competitions where the best performer is declared the winner, model comparisons center on understanding in some detail how the different modeling "architectures" have been applied to the common task. In this paper we announce a new model comparison effort that will illuminate the general features of cognitive architectures as they are applied to control problems in dynamic environments. We begin by briefly describing the task to be modeled, our motivation for selecting that task and what we expect the comparison to reveal. Next, we describe the programmatic details of the comparison, including a quick survey of the requirements for accessing, downloading and connecting different models to the simulated task environment. We conclude with remarks on the general value in this and other model comparisons for advancing the science of AGI development.

Copyright

© 2009, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Christian Lebiere
AU  - Cleotilde Gonzalez
AU  - Walter Warwick
PY  - 2009/06
DA  - 2009/06
TI  - A Comparative Approach to Understanding General Intelligence: Predicting Cognitive Performance in an Open-ended Dynamic Task
BT  - Proceedings of the 2nd Conference on Artificial General Intelligence (2009)
PB  - Atlantis Press
SP  - 7
EP  - 11
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2009.2
DO  - 10.2991/agi.2009.2
ID  - Lebiere2009/06
ER  -