Communications of the ACM - How the virtual inspires the real
The RoboCup Soccer Server and CMUnited: Implemented Infrastructure for MAS Research
Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
Cormas: Common-Pool Resources and Multi-agent Systems
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Scenario description for multi-agent simulation
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Can software agents influence human relations?: balance theory in agent-mediated communities
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Modeling agents and interactions in agricultural economics
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Advancing the Layered Approach to Agent-Based Crowd Simulation
Proceedings of the 22nd Workshop on Principles of Advanced and Distributed Simulation
Proceedings of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding
Evaluation and comparison of multi-agent based crowd simulation systems
Agents for games and simulations II
A methodological approach to mining and simulating data in complex information systems
Intelligent Data Analysis
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For an integrated simulation such as the natural environment affected by human society, it is indispensable to provide an integrated simulator that incorporates multiple computational models. We proposed a multi-layer socio-environmental simulation by layering the social interaction scenario on environmental simulation. For this simulation, we connect two different systems. One is a scenario description language Q, which is suitable for describing social interactions. Another is CORMAS, which models interactions between a natural environment and humans. The key idea is to realize a mapping between agents in different systems. This integration becomes possible by the salient feature of Q: users can write scenarios for controlling legacy agents in other systems. Moreover, we find that controlling the flow of information between the two systems can create various types of simulations. We also confirm the capability of CORMAS/Q, in the well-known Fire-Fighter domain.