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Theoretical results on reinforcement learning with temporally abstract options

https://doi.org/10.1007/bfb0026709
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9780470316887openalex-snapshot
Markov Decision Processes
inferredcites →https://doi.org/10.1007/bf00116249openalex-snapshot
Chunking in Soar: The anatomy of a general learning mechanism
inferredcites →https://doi.org/10.1007/bf00993104openalex-snapshot
Prioritized Sweeping: Reinforcement Learning with Less Data and Less Time
inferredcites →https://doi.org/10.1016/0004-3702(92)90058-6openalex-snapshot
Automatic programming of behavior-based robots using reinforcement learning
inferredcites →https://doi.org/10.1016/b978-1-55860-141-3.50030-4openalex-snapshot
Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming
inferredcites →https://doi.org/10.1016/b978-1-55860-247-2.50058-9openalex-snapshot
Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution Models
inferredcites →https://doi.org/10.1016/b978-1-55860-307-3.50028-9openalex-snapshot
Hierarchical Learning in Stochastic Domains: Preliminary Results
inferredcites →https://doi.org/10.1016/b978-1-55860-377-6.50072-4openalex-snapshot
TD Models: Modeling the World at a Mixture of Time Scales
inferredcites →https://doi.org/10.1016/s0921-8890(97)00044-4openalex-snapshot
A feedback control structure for on-line learning tasks
inferredcites →https://doi.org/10.1016/s1474-6670(17)38315-5openalex-snapshot
Reinforcement Learning
inferredcites →https://doi.org/10.1023/a:1022639103969openalex-snapshot
Chunking in Soar: The Anatomy of a General Learning Mechanism
inferredcites →https://doi.org/10.1108/k.1998.27.9.1093.3openalex-snapshot
Reinforcement Learning:
inferredcites →https://doi.org/10.1109/tnn.1998.712192openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1162/neco.1993.5.4.613openalex-snapshot
Improving Generalization for Temporal Difference Learning: The Successor Representation
inferredcites →https://doi.org/10.1177/105971239300100403openalex-snapshot
Efficient Learning and Planning Within the Dyna Framework
inferredcites →https://doi.org/10.2307/2291177openalex-snapshot
Markov Decision Processes: Discrete Stochastic Dynamic Programming.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Towards Motivated Reinforcement Learning
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The ghost of behaviorism: critical reflections on methodological limitations in the research of large language models psychology
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Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
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Structure in the Space of Value Functions
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Recent Advances in Hierarchical Reinforcement Learning
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Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
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Accelerating Reinforcement Learning by Composing Solutions of Automatically Identified Subtasks
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Searching for Plannable Domains can Speed up Reinforcement Learning
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