Conference paper Open Access

# Aspiration-based Perturbed Learning Automata

Chasparis, Georgios

### Citation Style Language JSON Export

{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.1186662",
"title": "Aspiration-based Perturbed Learning Automata",
"issued": {
"date-parts": [
[
2018,
3,
1
]
]
},
"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"
}
],
"type": "paper-conference",
"id": "1186662"
}
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