Caleb Ho

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Reinforcement Learning — 9 citations into it

Whom Caleb Ho trusts overall

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

1. Levente Kocsis
2. Thomas W. Anthony

Papers from Caleb Ho's perspective

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

1. Reinforcement Learning: An Introduction
2. Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search
3. Bandit Based Monte-Carlo Planning
4. A Survey of Monte Carlo Tree Search Methods
5. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
6. Metrics for Finite Markov Decision Processes
7. I and J
8. OpenSpiel: A Framework for Reinforcement Learning in Games
9. Bisimulation Metrics for Continuous Markov Decision Processes
10. Learning Invariant Representations for Reinforcement Learning without Reconstruction

Their papers

• Monte Carlo Tree Search With Iteratively Refining State Abstractions (2021) — 22 citations