scientific article; zbMATH DE number 7306889

MaRDI QIDQ5148991

Michael L. Littman, Lucas Lehnert

Publication date: 5 February 2021

Full work available at URL: https://arxiv.org/abs/1901.11437

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

model-based reinforcement learningstate representationsstate abstractionsuccessor features

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning

Uses Software

• TensorFlow

Cites Work

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• Equivalence notions and model minimization in Markov decision processes
• \({\mathcal Q}\)-learning
• Bisimulation Metrics for Continuous Markov Decision Processes
• A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
• Learning Theory and Kernel Machines

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