Log In Sign Up

Socially Intelligent Genetic Agents for the Emergence of Explicit Norms

by   Rishabh Agrawal, et al.

Norms help regulate a society. Norms may be explicit (represented in structured form) or implicit. We address the emergence of explicit norms by developing agents who provide and reason about explanations for norm violations in deciding sanctions and identifying alternative norms. These agents use a genetic algorithm to produce norms and reinforcement learning to learn the values of these norms. We find that applying explanations leads to norms that provide better cohesion and goal satisfaction for the agents. Our results are stable for societies with differing attitudes of generosity.


page 1

page 2

page 3

page 4


A Norm Emergence Framework for Normative MAS – Position Paper

Norm emergence is typically studied in the context of multiagent systems...

Norm Identification through Plan Recognition

Societal rules, as exemplified by norms, aim to provide a degree of beha...

Prosocial Norm Emergence in Multiagent Systems

Multiagent systems provide a basis of developing systems of autonomous e...

Linking sanctions to norms in practice

Within social simulation, we often want agents to interact both with lar...

Few self-involved agents among BC agents can lead to polarized local or global consensus

Social issues are generally discussed by highly-involved and less-involv...