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Particle filter is an effective tool for vehicle tracking. However, we need to maintain a large number of particles to keep a reasonable tracking accuracy for multi-target tracking in large scale state space. This paper proposes a new distributed mean-field-type filter to handle those noisy, partial-observed and high-dimensional data. The state space is decomposed and the particles are deployed locally...
We consider a dynamic routing problem where the objective of each user is to obtain flow policy that minimizes its long term cost. The framework differs from other related works which consider collection of static one shot games with dynamic cost function. Instead, we motivate our problem from the two basic facts: i) the path cost may not be exactly known in advance in dynamic environment unlike static;...
We develop an evolutionary approach for analyzing network formation between selfish users and collective users (coalition) who mutually adapt their membership. A dynamic process of coalition formation is described by coupled evolutionary game dynamics. We apply them to packet forwarding problem in multi-hop heterogeneous networks and opportunistic spectrum sensing in cognitive radio networks.
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