Social norms characterize collective and acceptable group conducts in human society. Furthermore, some social norms emerge from interactions of agents or humans. To achieve agent autonomy and make norm satisfaction explainable, we include emotions into the normative reasoning process, which evaluates whether to comply or violate a norm. Specifically, before selecting an action to execute, an agent observes the environment and infers the state and consequences with its internal states after norm satisfaction or violation of a social norm. Both norm satisfaction and violation provoke further emotions, and the subsequent emotions affect norm enforcement. This paper investigates how modeling emotions affect the emergence and robustness of social norms via social simulation experiments. We find that an ability in agents to consider emotional responses to the outcomes of norm satisfaction and violation (1) promotes norm compliance; and (2) improves societal welfare.
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Requirements for an Artificial Agent with Norm Competence
Human behavior is frequently guided by social and moral norms, and no human community can exist without norms. Robots that enter human societies must therefore behave in norm-conforming ways as well. However, currently there is no solid cognitive or computational model available of how human norms are represented, activated, and learned. We provide a conceptual and psychological analysis of key properties of human norms and identify the demands these properties put on any artificial agent that incorporates norms—demands on the format of norm representations, their structured organization, and their learning algorithms.
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- Award ID(s):
- 1717701
- PAR ID:
- 10170790
- Date Published:
- Journal Name:
- AIES '19: Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society
- Page Range / eLocation ID:
- 21 to 27
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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