Technical Note: \cal Q-Learning
Machine Learning
Emergence: from chaos to order
Emergence: from chaos to order
On agent-based software engineering
Artificial Intelligence
Where the action is: the foundations of embodied interaction
Where the action is: the foundations of embodied interaction
A new kind of science
Artificial Life: An Overview
Affect and machine design: Lessons for the development of autonomous machines
IBM Systems Journal
Influence of colearner agent gehavior on learner performance and attitudes
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Robotics and Autonomous Systems
Multi-agent role allocation: issues, approaches, and multiple perspectives
Autonomous Agents and Multi-Agent Systems
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When constructing multiagent systems, the designer may approach the system as a collection of individuals or may view the entire system as a whole. In addition to these approaches, it may be beneficial to consider the interactions between the individuals and the whole. Borrowing ideas from the notion of social construction and building on previous work in synthetic social construction, this paper presents a framework wherein autonomous agents engage in a dialectic relationship with the society of agents around them. In this framework, agents recognize patterns of social activity in their societies, group such patterns into institutions, and form computational representations of those institutions. The paper presents a design framework describing this method of institutionalization, some implementation suggestions, and a discussion of possible applications.