Ensembles of extreme learning machine networks for value prediction
نویسندگان
چکیده
Value prediction is an important subproblem of several reinforcement learning (RL) algorithms. In a previous work, it has been shown that the combination of least-squares temporal-difference learning with ELM (extreme learning machine) networks is a powerful method for value prediction in continuous-state problems. This work proposes the use of ensembles to improve the approximation capabilities of ELM networks in the context of RL.
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