We present an efficient approach for identifying, learning and modeling the policies of others during collaborative activities. In a set of experiments, we demonstrate that more accurate models of others' policies (or norms) can be developed more rapidly using various forms of evidence from argumentation-based dialogue.
|Title of host publication||Proceedings of the 9th Internatinal Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010)|
|Editors||Wiebe van der Hoek, Gal Kaminka, Michael Luck, Sandip Sen|
|Publisher||International Foundation for Autonomous Agents and Multiagent Systems|
|Number of pages||2|
|ISBN (Electronic)||0982657100, 9780982657119|
|Publication status||Published - 5 Oct 2010|
|Event||Ninth International Joint Conference on Autonomous Agents and Multiagent Systems - Toronto, Canada|
Duration: 10 May 2010 → …
|Conference||Ninth International Joint Conference on Autonomous Agents and Multiagent Systems|
|Period||10/05/10 → …|
Emele, C. D., Norman, T. J., Guerin, F., & Parsons, S. (2010). Learning policies through argumentation-derived evidence (extended abstract). In W. van der Hoek, G. Kaminka, M. Luck, & S. Sen (Eds.), Proceedings of the 9th Internatinal Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010) International Foundation for Autonomous Agents and Multiagent Systems.