Abstract
This paper focuses on the internal representation of norms and the necessary concepts required for normative decisionmaking in computational agents. We leverage the social science literature to integrate currently absent prevalent concepts of social expectations within the Expectation Event Calculus (EEC) and, in doing so, extend the formalism. Through the adopted terminology of expectations, we distinguish between descriptive and social norms, enabling a more comprehensive description of individual and collective behavior conditional on social expectations. We introduce complementary abstractions for normative attributes to demonstrate and explain why such a distinction between expectations enables richer normative scenarios to be modeled, which has yet to be shown in the EEC. We demonstrate this extension through a binarydecision social scenario. First, through a single-agent implementation driven by hardwired narratives. Secondly, we demonstrate the extension through a selection of multi-agent scenarios that showcase a change in behavior conditional on expectations. As a minimal implementation of social expectations, we conclude the paper with themes and open challenges as avenues for further research.