An Adaptive Architecture for Physical Agents

Authors:
Pat Langley
Affiliations:
Computational Learning Laboratory Center for the Study of Language and Information Stanford University
Venue:
IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Year:
2005

Citing 0
Cited 4

Providing agent support for collaborative systems: using a domain-oriented design method

International Journal of Agent-Oriented Software Engineering
Cognitive Architectures: Where do we go from here?

Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures

Neurocomputing
Towards computational models of artificial cognitive systems that can, in principle, pass the turing test

SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we describe ICARUS, an adaptive architecture for intelligent physical agents. We contrast the frameworkýs assumptions with those of earlier architectures, taking examples from an in-city driving task to illustrate our points. Key differences include primacy of perception and action over problem solving, separate memories for categories and skills, a hierarchical organization on both memories, strong correspondence between long-term and short-term structures, and cumulative learning of skill hierarchies. We support claims for ICARUSý generality by reporting our experience with driving and three other domains. In closing, we discuss limitations of the current architecture and propose extensions that would remedy them.