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Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective.
international conference on artificial intelligence and statistics, (2019)
Black-box optimizers that explore in parameter space have often been shown to outperform more sophisticated action space exploration methods developed specifically for the reinforcement learning problem. We examine these black-box methods closely to identify situations in which they are worse than action space exploration methods and thos...More
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