By Edited by Wolfgang Stolzmann, Edited by Stewart W. Wilson Edited by Pier Luca Lanzi
Those are the refereed post-proceedings of the 4th overseas Workshop on studying Classifier platforms, IWLCS 2001. the 1st half is dedicated to theoretical concerns, and the second one to functions in a number of fields corresponding to info mining, inventory buying and selling, and tool distribution networks.
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Extra info for Advances in learning classifier systems: 4th international workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001 : revised papers
Rather than a source of information about the environment modeled by the LCS, the population has been viewed as a necessary means to make accurate predictions or decisions. THEN rules, with associated metrics that describe the accuracy of these rules in explanation and prediction, two common tasks in data mining. This work describes an extension to an existing LCS design, EpiCS, that allows the assessment of the performance of each classifier in the population by incorporating two metrics traditionally associated with the evaluation of clinical diagnostic tests .
W. Classifier Fitness Based on Accuracy. Evolutionary Computation, 3(2), 149-175 (1995). A Minimal Model of Communication for a Multi-agent Classifier System ´ ee and Cathy Escazut Gilles En´ Laboratory I3S, Les algorithmes / Bˆ at. fr Abstract. Classiﬁer systems are rule-based systems dedicated to the learning of more or less complex tasks. They evolve toward a solution without any external help. When the problem is very intricate it is useful to have diﬀerent systems, each of them being in charge with an easier part of the problem.
The emergence of communication through synthetic evolution. To appear in Honavar, V. , and Balakrishnan K. ): Advances in evolutionary synthesis of neural systems. MIT Press. 21. Michel, O. (1995). ch/lami/team/michel/khep-sim/ ´ ee, G. and Escazut, C. (2001). A Minimal Model of Communication for Multi22. En´ Agent Systems. To appear in the proceedings of the 8th IEEE International Conference on Emerging Technologies and Factory Automation, Antibes France. A Representation for Accuracy-Based Assessment of Classifier System Prediction Performance John H.