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In many real-world multiagent applications such as distributed sensor nets, a network of agents is formed based on each agent's limited interactions with a small number of neighbors. While distributed POMDPs capture the real-world uncertainty in multiagent domains, they fail to exploit such locality of interaction. Distributed constraint optimization (DCOP)… (More)

Solving a coordination problem in a decentralized environment requires a large amount of resources and thus exploiting the innate system structure and external information as much as possible is necessary for such a problem to be solved in a computationally effective manner. This work proposes new techniques for saving communication and computational… (More)

In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations. Thus, selecting a subset of nodes to perform measurements whose results will closely mirror the results of having all the nodes perform measurements is an important problem. This… (More)

Many distributed constraint optimization (DCOP) algorithms include nodes' local maximization operation that searches for the optimal variable assignment in a limited context. When the variable domain is discrete, this operation is exponential in the number of associated variables and thus com-putationally challenging. McAuley's recent work on efficient… (More)

In this paper we propose a novel DCOP algorithm, called DJAO, that is able to efficiently find a solution with low communication overhead; this algorithm can be used for optimal and bounded approximate solutions by appropriately setting the error bounds. Our approach builds on distributed junction trees used in Action-GDL to represent independence relations… (More)

In situations where Bayesian networks (BN) inferencing approximation is allowable, we show how to reduce the amount of sensory observations necessary and in a multi-agent context the amount of agent communication. To achieve this, we introduce Pseudo-Independence, a relaxed independence relation that quantitatively differentiates the various degrees of… (More)

An organizationally adept agent (OAA) adjusts its behavior when given annotated organizational guidelines. More importantly, it can also determine when such guidelines become ineffective and proactively adapt its behavior to better achieve organizational objectives. We present the high-level aspects of this architecture and analyze its effectiveness using… (More)

This work proposes new techniques for saving communication and computational resources when solving distributed constraint optimization problems using the Max-Sum algorithm in an environment where system hardware resources are clustered. Solving a coordination problem in a decentralized environment requires a large amount of resources and thus exploiting… (More)

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