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• W2033606355 abstract "The paper presents an architecture that allows the reactive visual navigation via an unsupervised reinforcement learning. This objective is reached using Q-learning and a hierarchical approach to the developed architecture. Using these techniques requires a deviation from the Partially Observable Markov Decision Processes (POMDP) and some innovations: heuristic techniques for generalizing the experience and for treating the partial observability; a technique for the speed adjournment of the Q function; the definition of a special reinforcement policy adequate for learning a complex task without supervision. The result is a satisfactory learning of the navigation assignment in a simulated environment." @default.
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• W2033606355 date "2006-01-01" @default.
• W2033606355 modified "2023-09-26" @default.
• W2033606355 title "Navigation with memory in a partially observable environment" @default.
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• W2033606355 doi "https://doi.org/10.1016/j.robot.2005.09.015" @default.
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