Learning models of other agents using influence diagrams
UM '99 Proceedings of the seventh international conference on User modeling
Probabilistic Reasoning in Multi-Agent Systems: A Graphical Models Approach
Probabilistic Reasoning in Multi-Agent Systems: A Graphical Models Approach
Bayesian Update of Recursive Agent Models
User Modeling and User-Adapted Interaction
Rational Communication in Multi-Agent Environments
Autonomous Agents and Multi-Agent Systems
Optimal design in collaborative design network
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Communication management using abstraction in distributed Bayesian networks
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Learning to communicate in a decentralized environment
Autonomous Agents and Multi-Agent Systems
Tractable Optimal Multiagent Collaborative Design
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Dynamic multiagent probabilistic inference
International Journal of Approximate Reasoning
Solving transition independent decentralized Markov decision processes
Journal of Artificial Intelligence Research
Multi-agent influence diagrams for representing and solving games
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Asynchronous aggregation and consistency in distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
The complexity of decentralized control of Markov decision processes
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Multiagent bayesian forecasting of structural time-invariant dynamic systems with graphical models
International Journal of Approximate Reasoning
A framework and a mean-field algorithm for the local control of spatial processes
International Journal of Approximate Reasoning
Multiagent decision by partial evaluation
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
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Frameworks for cooperative multiagent decision making may be divided into those where each agent is assigned a single variable (SVFs) and those where each agent carries an internal model, which can be further divided into loosely coupled frameworks (LCFs) and tightly coupled frameworks (TCFs). In TCFs, agent communication interfaces render their subuniverses conditionally independent. In LCFs, either agents do not communicate or their messages are semantically less restricted. SVFs do not address the privacy issue well. LCF agents cannot draw from collective knowledge as well as TCF agents can. However, disproportional effort has been dedicated to SVFs and LCFs, which can be attributed partially to unawareness of the computational advantages of TCFs over performance, efficiency and privacy. This work aims to provide empirical evidence of such advantages by comparing recursive modeling method from LCFs and collaborative design network from TCFs, both of which are decision-theoretic and the latter of which is based on graphical models. We apply both to a testbed, multiagent expedition, resolve technical issues encountered, and report our experimental evaluation.