Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Causal Maps: Theory, Implementation, and Practical Applications in Multiagent Environments
IEEE Transactions on Knowledge and Data Engineering
Prominence convergence in the collective synchronization of situated multi-agents
Information Processing Letters
Compatibility between the local and social performances of multi-agent societies
Expert Systems with Applications: An International Journal
Contextual Resource Negotiation-Based Task Allocation and Load Balancing in Complex Software Systems
IEEE Transactions on Parallel and Distributed Systems
A model for collective strategy diffusion in agent social law evolution
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Concurrent collective strategy diffusion of multiagents: the spatial model and case study
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
A multi-agent coordination model for the variation of underlying network topology
Expert Systems with Applications: An International Journal
Multiagent Coordination Techniques for Complex Environments: The Case of a Fleet of Combat Ships
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Engineering Open Complex Agent Systems: A Case Study
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Evolutionary Computation
Ad hoc innovation: distributed decision making in ad hoc networks
IEEE Communications Magazine
Hi-index | 12.05 |
In previous work on collective motion, agents always tend to imitate the behavior strategies of higher ranks; this model is called rank-based strategy diffusion. Unfortunately, this model is, by itself, insufficient in causal multiagent societies where agents may have causal links with each other. In causal environments, agents will develop positive (or negative) attitudes (favor) about those who can increase (or decrease) their own utilities. Naturally, for collective motion, agents will be inclined to imitate those who are well-favored and avoid those who are disfavored. This paper presents the concept of favor in causal environments, and presents a model for favor-based strategy diffusion. In the proposed model, agents in causal environments are inclined to associate with and imitate the strategies of those who are well-favored. Obviously, such diffusion effects well reflect the impact of causal relations in the real world.