Carlos Segami

Management Science and Operations Research

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

• Management Science and Operations Research — 15 citations into it
• Artificial Intelligence — 11 citations into it
• Reinforcement Learning — 10 citations into it

Whom Carlos Segami trusts overall

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

1. Michael L. Littman

Who trusts Carlos Segami overall

1. Tuomas Sandholm
2. Erik Zawadzki

Papers from Carlos Segami's perspective

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

1. Markov Games as a Framework for Multi-Agent Reinforcement Learning
2. Markov Decision Processes: Discrete Stochastic Dynamic Programming
3. Reinforcement Learning: An Introduction
4. Asynchronous Methods for Deep Reinforcement Learning
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. The Theory of Learning in Games
7. ImageNet classification with deep convolutional neural networks
8. Correlated Q-Learning
9. Reinforcement Learning: A Survey
10. Temporal Difference Learning and TD-Gammon

Their papers

• Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm