TY - GEN
T1 - Teaching social behavior through human reinforcement for ad hoc teamwork-the star framework
AU - Alkoby, Shani
AU - Rath, Avilash
AU - Stone, Peter
N1 - Publisher Copyright:
© 2019 International Foundation for Autonomous Agents and Multiagent Systems. All rights reserved.
PY - 2019
Y1 - 2019
N2 - As AI technology continues to develop, more and more agents will become capable of long term autonomy alongside people. Thus, a recent line of research has studied the problem of teaching autonomous agents the concept of ethics and human social norms. Most existing work considers the case of an individual agent attempting to learn a predefined set of rules. In reality however, social norms are not always pre-defined and are very difficult to represent algorithmically. Moreover, the basic idea behind the social norms concept is ensuring that one's actions do not negatively influence others' utilities, which is inherently a multiagent concept. Thus, here we investigate a way to teach agents, as a team, how to act according to human social norms. In this research, we introduce the star framework used to teach an ad hoc team of agents to act in accordance with human social norms. Using a hybrid team (agents and people), when taking an action considered to be socially unacceptable, the agents receive negative feedback from the human teammate(s) who has(have) an awareness of the team's norms. We view star as an important step towards teaching agents to act more consistently with respect to human morality.
AB - As AI technology continues to develop, more and more agents will become capable of long term autonomy alongside people. Thus, a recent line of research has studied the problem of teaching autonomous agents the concept of ethics and human social norms. Most existing work considers the case of an individual agent attempting to learn a predefined set of rules. In reality however, social norms are not always pre-defined and are very difficult to represent algorithmically. Moreover, the basic idea behind the social norms concept is ensuring that one's actions do not negatively influence others' utilities, which is inherently a multiagent concept. Thus, here we investigate a way to teach agents, as a team, how to act according to human social norms. In this research, we introduce the star framework used to teach an ad hoc team of agents to act in accordance with human social norms. Using a hybrid team (agents and people), when taking an action considered to be socially unacceptable, the agents receive negative feedback from the human teammate(s) who has(have) an awareness of the team's norms. We view star as an important step towards teaching agents to act more consistently with respect to human morality.
KW - Ad hoc
KW - Reinforcement learning
KW - Social norms
UR - http://www.scopus.com/inward/record.url?scp=85074999964&partnerID=8YFLogxK
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AN - SCOPUS:85074999964
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 1773
EP - 1775
BT - 18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
T2 - 18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
Y2 - 13 May 2019 through 17 May 2019
ER -