Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
On the emergence of social conventions: modeling, analysis, and simulations
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Evolving multi-agents using a self-organizing genetic algorithm
Applied Mathematics and Computation
Multiagent reinforcement learning and self-organization in a network of agents
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Emergence of norms through social learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The role of clustering on the emergence of efficient social conventions
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Force Versus Majority: A Comparison in Convention Emergence Efficiency
Coordination, Organizations, Institutions and Norms in Agent Systems IV
An infection-based mechanism in large convention spaces
COIN'09 Proceedings of the 5th international conference on Coordination, organizations, institutions, and norms in agent systems
Robust coordination in large convention spaces
AI Communications - European Workshop on Multi-Agent Systems (EUMAS) 2009
Manipulating convention emergence using influencer agents
Autonomous Agents and Multi-Agent Systems
| Hi-index | 0.00 |
Norms have become a common mechanism to regulate the behavior of agents in multi-agent systems (MAS). However, establishing a stable set of norms is not trivial, particularly in dynamic environments, under changing (and unpredictable) conditions. We propose a computational model that facilitates agents in a MAS to collaboratively evolve their norms, reconfigure themselves, to adapt to changing conditions. Our approach borrows from the social contagion phenomenon to exploit the notion of positive infection: agents with good behaviors become infectious to spread their norms in the agent society. By combining infection and innovation, a mechanism allowing agents exploring new norms, our computational model helps MAS to continuously stabilize despite perturbations.