Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
COGENT: cognitive agent to amplify human perception and cognition
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Satisficing Games and Decision Making: With Applications to Engineering and Computer Science
Satisficing Games and Decision Making: With Applications to Engineering and Computer Science
Service-Oriented Architecture: Concepts, Technology, and Design
Service-Oriented Architecture: Concepts, Technology, and Design
Modeling one human decision maker with a multi-agent system: the CODAGE approach
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Cognitive agents based simulation for decisions regarding human team composition
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
PsychSim: modeling theory of mind with decision-theoretic agents
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Socially intelligent reasoning for autonomous agents
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On the engineering of agent-based simulations of social activities with social networks
Information and Software Technology
| Hi-index | 0.00 |
Agent-based modeling of human social behavior is an increasingly important research area. Many fully functional multi-agent systems have been developed and have been put to use over the years. But efficient scalable and robust social systems are difficult to engineer, both from the modeling perspective and the implementation perspective. There exist three important difficulties. First, the system needs to have an adaptable agent framework that can successfully make intuitive and deliberative decisions much like a real social participant would. Secondly, the system must have a robust architecture that not only ensures its functioning no matter the simulation, but also provides an easily understood interface that researchers can interact with while running their simulations. Finally, the system must be effectively distributed to handle the necessary number of agents that social research requires to obtain meaningful results. This paper presents our work on creating a multi-agent simulation for social agents that would overcome these three difficulties. Lastly, we present a simulation to test the system and provide the results of that simulation.