Norms and Learning in Probabilistic Logic-Based Agents

  • Régis Riveret
  • Antonino Rotolo
  • Giovanni Sartor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7393)

Abstract

This paper proposes a new simulation approach for investigating phenomena such as norm emergence and internalization in large groups of learning agents. We define a probabilistic defeasible logic instantiating Dung’s argumentation framework. Rules of this logic are attached to probabilities and describe the agents’ minds and behaviour. We thus adopt the paradigm of reinforcement learning over this probability distribution to allow agents to adapt to their environment.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Régis Riveret
    • 1
  • Antonino Rotolo
    • 2
  • Giovanni Sartor
    • 2
    • 3
  1. 1.Department of Electrical and Electronic EngineeringImperial College of Science, Technology and MedicineLondonUK
  2. 2.CIRSFIDUniversity of BolognaItaly
  3. 3.European University InstituteFlorenceItaly

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