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Apr 6, 2019 � In this paper, we consider a challenging setting where an agent and an expert use different actions from each other. We assume that the agent�...
A challenging setting where an agent and an expert use different actions from each other is considered, and a method which gradually balances between the�...
In this paper, we consider a challenging setting where an agent and an expert use different actions from each other. We assume that the agent has access to a�...
In this paper, we consider a challenging setting where an agent and an expert use different actions from each other. We assume that the agent has access to a�...
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"Reinforced Imitation in Heterogeneous Action Space" Zolna et al.: https://arxiv.org/abs/1904.03438 #MachineLearning #ArtificialIntelligence...
Oct 18, 2024 � Abstract:In this paper, we consider a transfer reinforcement learning problem involving agents with different action spaces.
We propose two extensions that permit imitation of agents with heterogeneous actions: feasibility testing, which detects infeasible mentor actions, and k-step�...
Imitation learning is an effective alternative approach to learn a policy when the reward function is sparse. In this paper, we …
<Reinforced Imitation in Heterogeneous Action Space>, by Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio, Sungjin Ahn and Pedro O. Pinheiro, 2019. <Policy�...
Reinforced Imitation in Heterogeneous Action Space. Imitation learning is an effective alternative�...