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Sample Efficient Multiagent Learning in the Presence of Markovian Agents

Sample Efficient Multiagent Learning in the Presence of Markovian Agents

Doran Chakraborty

134,50 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2016
Materia
Inteligencia artificial
ISBN:
9783319352930
134,50 €
IVA incluido
Disponible

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Sobre IBD

The problem of Multiagent Learning (or MAL) is concerned with the study of how intelligent entities can learn and adapt in the presence of other such entities that are simultaneously adapting. The problem is often studied in the stylized settings provided by repeated matrix games (a.k.a. normal form games). The goal of this book is to develop MAL algorithms for such a setting that achieve a new set of objectives which have not been previously achieved. In particular this book deals with learning in the presence of a new class of agent behavior that has not been studied or modeled before in a MAL context: Markovian agent behavior. Several new challenges arise when interacting with this particular class of agents. The book takes a series of steps towards building completely autonomous learning algorithms that maximize utility while interacting with such agents. Each algorithm is meticulously specified with a thorough formal treatment that elucidates its key theoretical properties.

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Otros libros del autor

  • Sample Efficient Multiagent Learning in the Presence of Markovian Agents
    Doran Chakraborty
    The problem of Multiagent Learning (or MAL) is concerned with the study of how intelligent entities can learn and adapt in the presence of other such entities that are simultaneously adapting. The problem is often studied in the stylized settings provided by repeated matrix games (a.k.a. normal form games). The goal of this book is to develop MAL algorithms for such a setting t...