%0 Conference Paper %1 cranefield2015bayesian %A Cranefield, Stephen %A Meneguzzi, Felipe %A Oren, Nir %A Savarimuthu, Bastin Tony Roy %B Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems %D 2015 %I IFAAMAS %K myown %P 1743-1744 %T A Bayesian Approach to Norm Identification (Extended Abstract) %U http://www.aamas2015.com/en/AAMAS_2015_USB/aamas/p1743.pdf %X When entering a system, an agent should be aware of the obligations and prohibitions (collectively norms) that will affect it. Several solutions to this norm identification problem have been proposed, which make use of observations of either other’s norm compliant, or norm violating, behaviour. These solutions fail in situations where norms are typically violated, or complied with, respectively. In this paper we propose a Bayesian approach to norm identification which operates by learning from both norm compliant and norm violating behaviour. By utilising both types of behaviour, our work not only overcomes a major limitation of existing approaches, but also yields improved performance over the state-of-the-art. We evaluate its effectiveness empirically, showing, under certain conditions, high accuracy scores.

@inproceedings{cranefield2015bayesian, abstract = {When entering a system, an agent should be aware of the obligations and prohibitions (collectively norms) that will affect it. Several solutions to this norm identification problem have been proposed, which make use of observations of either other’s norm compliant, or norm violating, behaviour. These solutions fail in situations where norms are typically violated, or complied with, respectively. In this paper we propose a Bayesian approach to norm identification which operates by learning from both norm compliant and norm violating behaviour. By utilising both types of behaviour, our work not only overcomes a major limitation of existing approaches, but also yields improved performance over the state-of-the-art. We evaluate its effectiveness empirically, showing, under certain conditions, high accuracy scores.}, added-at = {2015-05-04T02:55:31.000+0200}, author = {Cranefield, Stephen and Meneguzzi, Felipe and Oren, Nir and Savarimuthu, Bastin Tony Roy}, biburl = {https://www.bibsonomy.org/bibtex/29ac3d5c76d8bab2e738d35639cd74561/scranefield}, booktitle = {Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems}, interhash = {e8ce9c63935fc5749c0dab7612cc1acc}, intrahash = {9ac3d5c76d8bab2e738d35639cd74561}, keywords = {myown}, pages = {1743-1744}, publisher = {IFAAMAS}, timestamp = {2015-05-04T02:55:31.000+0200}, title = {A Bayesian Approach to Norm Identification (Extended Abstract) }, url = {http://www.aamas2015.com/en/AAMAS_2015_USB/aamas/p1743.pdf}, year = 2015 }