TD-regularized actor-critic methods

DOI10.1007/s10994-019-05788-0zbMath1493.68313arXiv1812.08288OpenAlexW3104595455WikidataQ128334424 ScholiaQ128334424MaRDI QIDQ2320580

Mohammad Emtiyaz Khan, Jan Peters, Voot Tangkaratt, Simone Parisi

Publication date: 23 August 2019

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1812.08288

zbMATH Keywords

reinforcement learningactor-critictemporal difference

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Markov and semi-Markov decision processes (90C40) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (3)

Optimistic reinforcement learning by forward Kullback-Leibler divergence optimization ⋮ On the sample complexity of actor-critic method for reinforcement learning with function approximation ⋮ td-reg

Uses Software

• OpenAI Gym
• Adam
• GitHub
• MuJoCo

Cites Work

• Simple statistical gradient-following algorithms for connectionist reinforcement learning
• Q( $$\lambda $$ ) with Off-Policy Corrections
• OnActor-Critic Algorithms
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