Peter Stone's Selected Publications

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Reasoning about Hypothetical Agent Behaviours and their Parameters

Stefano Albrecht and Peter Stone. Reasoning about Hypothetical Agent Behaviours and their Parameters. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
Available from IFAAMAS and from ACM

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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.

BibTeX Entry

@inproceedings{AAMAS17-Albrecht,
  title = {Reasoning about Hypothetical Agent Behaviours and their Parameters},
  author = {Stefano Albrecht and Peter Stone},
  booktitle = {Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-17)},
  location = {S\~ao Paulo, Brazil},
  month = {May},
  year = {2017},
  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.},
  wwwnote={Available from <a href="http://www.ifaamas.org/Proceedings/aamas2017/pdfs/p547.pdf">IFAAMAS</a> and from <a href="https://dl.acm.org/citation.cfm?id=3091206&dl=ACM&coll=DL">ACM</a>},
}

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