Reinforcement Learning in Continuous Time and Space
Neural Computation
Neural-based downlink scheduling algorithm for broadband wireless networks
Computer Communications
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ARRAY(0x83fc18c) hierarchical or multi-level planning and reinforcement learning. In this paper we treat only the prediction problem--that of learning a model and value function for the case of fixed agent behavior. Within this context, we establish the theoretical foundations of multi-scale models and derive TD algorithms for learning them. Two small computational experiments are presented to test and illustrate the theory. This work is an extension and generalization of the work of Singh (1992), Dayan (1993), and Sutton and Pinette (1985).