New Paper on Ad-hoc Teamwork

Our work “On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork” was recently published at the Journal Autonomous Agents and Multi-Agent Systems (JAAMAS). It presents OEATE, a novel algorithm for online estimation of teammates’ type and parameters in decentralised task execution.

The paper is freely available at https://link.springer.com/article/10.1007/s10458-022-09571-9. The source code, built using our AdLeap-MAS framework, is available on Github.