Norms and learning in probabilistic logic-based agents

  • Authors:
  • Régis Riveret;Antonino Rotolo;Giovanni Sartor

  • Affiliations:
  • Department of Electrical and Electronic Engineering, Imperial College of Science, Technology and Medicine, London, UK;CIRSFID, University of Bologna, Italy;CIRSFID, University of Bologna, Italy,European University Institute, Florence, Italy

  • Venue:
  • DEON'12 Proceedings of the 11th international conference on Deontic Logic in Computer Science
  • Year:
  • 2012

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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.