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Peter-Stoneagent-modelling
2020
Stefano V. Albrecht, Peter Stone, Michael P. Wellman
Special Issue on Autonomous Agents Modelling Other Agents: Guest Editorial
Artificial Intelligence, 2020
Abstract | BibTex | Publisher | Special Issue
AIJsurveyagent-modelling
Abstract:
Much research in artificial intelligence is concerned with enabling autonomous agents to reason about various aspects of other agents (such as their beliefs, goals, plans, or decisions) and to utilise such reasoning for effective interaction. This special issue contains new technical contributions addressing open problems in autonomous agents modelling other agents, as well as research perspectives about current developments, challenges, and future directions.
@article{albrecht2020special,
title = {Special Issue on Autonomous Agents Modelling Other Agents: Guest Editorial},
author = {Stefano V. Albrecht and Peter Stone and Michael P. Wellman},
journal = {Artificial Intelligence},
volume = {285},
year = {2020},
publisher = {Elsevier},
url = {https://doi.org/10.1016/j.artint.2020.103292}
}
2018
Stefano V. Albrecht, Peter Stone
Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems
Artificial Intelligence, 2018
Abstract | BibTex | arXiv | Publisher
AIJsurveyagent-modellinggoal-recognition
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.
@article{ albrecht2018modelling,
title = {Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems},
author = {Stefano V. Albrecht and Peter Stone},
journal = {Artificial Intelligence},
volume = {258},
pages = {66--95},
year = {2018},
publisher = {Elsevier},
note = {DOI: 10.1016/j.artint.2018.01.002}
}
2017
Stefano V. Albrecht, Peter Stone
Reasoning about Hypothetical Agent Behaviours and their Parameters
International Conference on Autonomous Agents and Multiagent Systems, 2017
Abstract | BibTex | arXiv
AAMASad-hoc-teamworkagent-modelling
Abstract:
Agents can achieve effective interaction with previously unknown other agents by maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may have. A current limitation in this method is that it does not recognise parameters within type specifications, because types are viewed as blackbox mappings from interaction histories to probability distributions over actions. In this work, we propose a general method which allows an agent to reason about both the relative likelihood of types and the values of any bounded continuous parameters within types. The method maintains individual parameter estimates for each type and selectively updates the estimates for some types after each observation. We propose different methods for the selection of types and the estimation of parameter values. The proposed methods are evaluated in detailed experiments, showing that updating the parameter estimates of a single type after each observation can be sufficient to achieve good performance.
@inproceedings{ albrecht2017reasoning,
title = {Reasoning about Hypothetical Agent Behaviours and their Parameters},
author = {Stefano V. Albrecht and Peter Stone},
booktitle = {Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems},
pages = {547--555},
year = {2017}
}