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Coordinated inductive learning using argumentation-based communication

AuthorsOntañón, Santiago; Plaza, Enric
KeywordsLearning systems
Multi agent systems
Inductive learning
Computational argumentation
Issue DateMar-2015
CitationAutonomous Agents and Multi-Agent Systems, 29 (2): 266-304, 2015
AbstractThis paper focuses on coordinated inductive learning, concerning how agents with inductive learning capabilities can coordinate their learnt hypotheses with other agents. Coordination in this context means that the hypothesis learnt by one agent is consistent with the data known to the other agents. In order to address this problem, we present A-MAIL, an argumentation approach for agents to argue about hypotheses learnt by induction. A-MAIL integrates, in a single framework, the capabilities of learning from experience, communication, hypothesis revision and argumentation. Therefore, the A-MAIL approach is one step further in achieving autonomous agents with learning capabilities which can use, communicate and reason about the knowledge they learn from examples. © 2014, The Author(s).
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