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Erschienen in: KI - Künstliche Intelligenz 3/2014

01.08.2014 | Technical Contribution

A Survey of Multi-Agent Decision Making

verfasst von: Nils Bulling

Erschienen in: KI - Künstliche Intelligenz | Ausgabe 3/2014

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Abstract

In this article we give a high-level overview of various aspects relevant to multi-agent decision making. Classical decision theory makes the start. Then, we introduce multi-agent decision making, focussing on game theory, complex decision making, and on intelligent agents. Afterwards, we discuss methods for reaching agreements interactively, e.g. by negotiation, bargaining, and argumentation, followed by approaches to coordinate and to control agents’ decision making.

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Fußnoten
1
Acting strategically means, when acting an agent takes into consideration the behavior and motivations of other agents, specially how they will possibly react/respond to performed actions.
 
2
In this context, actions are also called strategies.
 
3
Goals can also be seen as abstractions of outcomes with their utility—those which are satisfactory for the agent [145].
 
4
Often, more general preference relations over outcomes are considered, cf. [99].
 
5
Social choice functions are also defined over preference relations [99] or agent types which characterize agents’ preferences  [141]; or they map to sets of outcomes [24, 99]. The latter type is sometimes called social choice rule, but the notation is not coherent in the literature.
 
6
In general, this can be defined for any other solution concept, e.g. a Nash equilibrium.
 
7
In the literature there are alternative definitions, e.g. when social choice rules are considered it is required that each possible outcome can be obtained by some equilibrium strategy; moreover, often the considered utility functions are taken from a restricted set rather than from the set of all possible functions, cf. [99, 141].
 
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Metadaten
Titel
A Survey of Multi-Agent Decision Making
verfasst von
Nils Bulling
Publikationsdatum
01.08.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
KI - Künstliche Intelligenz / Ausgabe 3/2014
Print ISSN: 0933-1875
Elektronische ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-014-0314-3

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