An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions

DOI10.1162/NECO_a_00808zbMath1472.68149OpenAlexW2225522132WikidataQ47600318 ScholiaQ47600318MaRDI QIDQ5380403

Kohei Hatano, Yao Ma, Tingting Zhao, Masashi Sugiyama

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_00808

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Markov and semi-Markov decision processes (90C40) Online algorithms; streaming algorithms (68W27)

Related Items (1)

An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions

Cites Work

• Simple statistical gradient-following algorithms for connectionist reinforcement learning
• Efficient algorithms for online decision problems
• Online Markov Decision Processes Under Bandit Feedback
• Online Markov Decision Processes
• Markov Decision Processes with Arbitrary Reward Processes
• Logarithmic Regret Algorithms for Online Convex Optimization
• An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions
• Unnamed Item
• Unnamed Item

This page was built for publication: An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions