Yoonheui Kim

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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)
The Max-Sum algorithm is a constraint optimization algorithm using message passing that can be configured to work in an approximate mode. It has been shown that in this mode it compares well with other approximate distributed optimization approaches. We used the approximate Max-Sum algorithm to coordinate adaptive radars for real-time weather sensing. When(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 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 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)
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)
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. A central OAA tenet is a clear separation between operational decision making (the detailed(More)