The impact of locality and authority on emergent conventions: initial observations
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
On the emergence of social conventions: modeling, analysis, and simulations
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Emergence of social conventions in complex networks
Artificial Intelligence
The Origins of Ontologies and Communication Conventions in Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems
Co-Learning and the Evolution of Social Acitivity
Co-Learning and the Evolution of Social Acitivity
Emergence of coordination in scale-free networks
Web Intelligence and Agent Systems
A unified framework for multi-agent agreement
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Infection-based self-configuration in agent societies
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
The role of clustering on the emergence of efficient social conventions
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Context Switching versus Context Permeability in Multiple Social Networks
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Robust convention emergence in social networks through self-reinforcing structures dissolution
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
| Hi-index | 0.00 |
In open societies such as multi-agent systems, it is important that coordination among the several actors is achieved efficiently. One economical way of capturing that aspiration is consensus: social conventions and lexicons are good examples of coordinating systems, where uniformity promotes shared expectations of behavior and shared meanings. We are particularly interested in consensus that is achieved without any central control or ruling, through decentralized mechanisms that prove to be effective, efficient, and robust. The nature of interactions and also the nature of society configurations may promote or inhibit consensual emergence. Traditionally, preference to adopt the most seen choices (the majority option) has dominated the emergence convention research in multi-agents, being analyzed along different social topologies. Recently, we have introduced a different type of interaction, based on force, where force is not defined a priori but evolves dynamically. We compare the Majority class of choice update against Force based interactions, along three dimensions: types of encounters, rules of interaction and network topologies. Our experiments show that interactions based on Force are significantly more efficient (fewer encounters) for group decision making.