Distributed Artificial Intelligence
Distributed Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Communication in reactive multiagent robotic systems
Autonomous Robots
Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Making Organizational Learning Operational: Implications from Learning Classifier Systems
Computational & Mathematical Organization Theory
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Interpretation by Implementation for Understanding a Multiagent Organization
Computational & Mathematical Organization Theory
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This paper addresses a big issue of a multiagent design principle by exploring our model in terms of its generality, scalability, and performance. To investigate these aspects in our model, we apply it into another domain, analyze its characteristics in large-scale problems, and compare its performance with that one of conventional models. Intensive simulations on a complex domain problem reveal the following implications: (1) our model shows its effectiveness in another domain, maintains its effectiveness in large-scale problems, and achieve a better performance than conventional models; (2) three key elements derived from our model have the potential to be important and essential factors towards multiagent design principles; and (3) the interpretation of general concepts from a computational viewpoint is one of the useful ways of addressing multiagent design principles.