Autonomous Agents Modelling Other Agents: A Comprehensive Survey and
Open Problems
S. Albrecht, and P. Stone. (2017)cite arxiv:1709.08071Comment: 42 pages, submitted for review to Artificial Intelligence Journal. Keywords: multiagent systems, agent modelling, opponent modelling, survey, open problems.
Abstract
Much research in artificial intelligence is concerned with the development of
autonomous agents that can interact effectively with other agents. An important
aspect of such agents is the ability to reason about the behaviours of other
agents, by constructing models which make predictions about various properties
of interest (such as actions, goals, beliefs) of the modelled agents. A variety
of modelling approaches now exist which vary widely in their methodology and
underlying assumptions, catering to the needs of the different sub-communities
within which they were developed and reflecting the different practical uses
for which they are intended. The purpose of the present article is to provide a
comprehensive survey of the salient modelling methods which can be found in the
literature. The article concludes with a discussion of open problems which may
form the basis for fruitful future research.
Description
[1709.08071] Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems
%0 Generic
%1 albrecht2017autonomous
%A Albrecht, Stefano V.
%A Stone, Peter
%D 2017
%K 2017 artificial-intelligence arxiv collection paper problem reinforcement-learning research survey
%T Autonomous Agents Modelling Other Agents: A Comprehensive Survey and
Open Problems
%U http://arxiv.org/abs/1709.08071
%X Much research in artificial intelligence is concerned with the development of
autonomous agents that can interact effectively with other agents. An important
aspect of such agents is the ability to reason about the behaviours of other
agents, by constructing models which make predictions about various properties
of interest (such as actions, goals, beliefs) of the modelled agents. A variety
of modelling approaches now exist which vary widely in their methodology and
underlying assumptions, catering to the needs of the different sub-communities
within which they were developed and reflecting the different practical uses
for which they are intended. The purpose of the present article is to provide a
comprehensive survey of the salient modelling methods which can be found in the
literature. The article concludes with a discussion of open problems which may
form the basis for fruitful future research.
@misc{albrecht2017autonomous,
abstract = {Much research in artificial intelligence is concerned with the development of
autonomous agents that can interact effectively with other agents. An important
aspect of such agents is the ability to reason about the behaviours of other
agents, by constructing models which make predictions about various properties
of interest (such as actions, goals, beliefs) of the modelled agents. A variety
of modelling approaches now exist which vary widely in their methodology and
underlying assumptions, catering to the needs of the different sub-communities
within which they were developed and reflecting the different practical uses
for which they are intended. The purpose of the present article is to provide a
comprehensive survey of the salient modelling methods which can be found in the
literature. The article concludes with a discussion of open problems which may
form the basis for fruitful future research.},
added-at = {2017-11-29T18:46:37.000+0100},
author = {Albrecht, Stefano V. and Stone, Peter},
biburl = {https://www.bibsonomy.org/bibtex/2a4338c83cdcd618e354003920cdd24be/achakraborty},
description = {[1709.08071] Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems},
interhash = {66d066daea3bcae4206fa0c18aa0657c},
intrahash = {a4338c83cdcd618e354003920cdd24be},
keywords = {2017 artificial-intelligence arxiv collection paper problem reinforcement-learning research survey},
note = {cite arxiv:1709.08071Comment: 42 pages, submitted for review to Artificial Intelligence Journal. Keywords: multiagent systems, agent modelling, opponent modelling, survey, open problems},
timestamp = {2017-11-29T18:47:26.000+0100},
title = {Autonomous Agents Modelling Other Agents: A Comprehensive Survey and
Open Problems},
url = {http://arxiv.org/abs/1709.08071},
year = 2017
}