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Parameterized MDPs and Reinforcement Learning Problems -- A Maximum Entropy Principle Based Framework
The central idea underlying our framework is to quantify exploration in terms of the Shannon Entropy of the trajectories under the MDP and determine the stochastic policy that maximizes it while guaranteeing a low value of the expected cost along a trajectory.
A Deterministic Annealing Approach to the Multiple Traveling Salesmen and Related Problems
This paper presents a novel and efficient heuristic framework for approximating the solutions to the multiple traveling salesmen problem (m-TSP) and other variants on the TSP.
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