Conference paper Open Access

Aspiration-based Perturbed Learning Automata

Chasparis, Georgios


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{
  "DOI": "10.5281/zenodo.1186662", 
  "abstract": "<p>This paper introduces a novel payoff-based learning scheme for distributed optimization in repeatedly-played strategic-form games. Standard reinforcement-based learning exhibits several limitations with respect to their asymptotic stability. For example, in two-player coordination games, payoff-dominant (or efficient) Nash equilibria may not be stochastically stable. In this work, we present an extension of perturbed learning automata, namely aspiration-based perturbed learning automata (APLA) that overcomes these limitations. We provide a stochastic stability analysis in multi-player coordination games. In the case of two-player coordination games, we show that the payoff-dominant Nash equilibrium is the unique stochastically stable state.</p>", 
  "author": [
    {
      "family": "Chasparis, Georgios"
    }
  ], 
  "id": "1186662", 
  "issued": {
    "date-parts": [
      [
        2018, 
        3, 
        1
      ]
    ]
  }, 
  "publisher": "Zenodo", 
  "title": "Aspiration-based Perturbed Learning Automata", 
  "type": "paper-conference"
}
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