UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
Reasoning about Hypothetical Agent Behaviours and their Parameters (2017)
Stefano Albrecht
and
Peter Stone
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.
View:
PDF
,
HTML
Citation:
In
Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-17)
, Sao Paulo, Brazil, May 2017.
Bibtex:
@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)}, month={May}, address={Sao Paulo, Brazil}, url="http://www.cs.utexas.edu/users/ai-lab?albrecht:aamas17", year={2017} }
People
Stefano Albrecht
Postdoctoral Alumni
svalb [at] cs utexas edu
Peter Stone
Faculty
pstone [at] cs utexas edu
Areas of Interest
Ad Hoc Teamwork
Labs
Learning Agents