Nicholas Haltmeyer

Reinforcement Learning · 2015

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 10 citations into it

Whom Nicholas Haltmeyer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Andrew Barto
2. Christopher J. C. H. Watkins
3. Marc Pickett
4. Carlos Diuk
5. Richard S. Sutton

Papers from Nicholas Haltmeyer's perspective

Ordered by how strongly the researchers Nicholas Haltmeyer trusts endorse each paper. Same corpus, a different order for every researcher.

1. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
2. Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density
3. Building Portable Options: Skill Transfer in Reinforcement Learning
4. An object-oriented representation for efficient reinforcement learning
5. Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning
6. PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning
7. Transfer in Reinforcement Learning via Shared Features
8. Q-learning
9. Dynamic abstraction in reinforcement learning via clustering
10. PAC-inspired Option Discovery in Lifelong Reinforcement Learning

Their papers

• Portable Option Discovery for Automated Learning Transfer in Object-Oriented Markov Decision Processes (2015) — 34 citations