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Experiments with Multiple BDI Agents with Dynamic Learning Capabilities

  • Amelia BădicăEmail author
  • Costin Bădică
  • Maria Ganzha
  • Mirjana Ivanović
  • Marcin Paprzycki
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 616)

Abstract

In this paper we show how multiple BDI agents, enhanced with temporal difference learning capabilities, learn their utility function, while they are concurrently exploring an uncertain environment. We focus on the programming aspects of the agents using the Jason agent-oriented programming language. We also provide experimental results showing the behavior of multiple agents acting in a Markovian grid environment. We consider agents with the perception function affected by the intermittent faults and Gaussian noise, as well as agents for which their action function is not always successful.

Keywords

BDI agent Reinforcement learning Agent-oriented programming 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Amelia Bădică
    • 1
    Email author
  • Costin Bădică
    • 1
  • Maria Ganzha
    • 2
  • Mirjana Ivanović
    • 3
  • Marcin Paprzycki
    • 2
  1. 1.University of CraiovaCraiovaRomania
  2. 2.Polish Academy of Sciences, Systems Research InstituteWarszawaPoland
  3. 3.Faculty of SciencesNovi SadSerbia

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