منابع مشابه
CMAC Models Learn to Play
Traditional reinforcement learning methods require a function approx-imator (FA) for learning value functions in large or continuous state spaces. We describe a novel combination of CMAC-based FAs and adap-tive world models (WMs) estimating transition probabilities and rewards. Simple variants are tested in multiagent soccer environments where they outperform the evolutionary method PIPE which ...
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ژورنال
عنوان ژورنال: Nature Electronics
سال: 2019
ISSN: 2520-1131
DOI: 10.1038/s41928-019-0224-3