Dipyaman Banerjee

Reinforcement Learning · 2007

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 7 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Dipyaman Banerjee trusts overall

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

1. Michael L. Littman
2. Tuomas Sandholm
3. Michael H. Bowling
4. Nick Littlestone
5. Drew Fudenberg
6. Satinder Singh
7. Manuela M. Veloso
8. Michael Kearns
9. David K. Levine
10. Manfred K. Warmuth

Who trusts Dipyaman Banerjee overall

1. Stefano V. Albrecht
2. Enrique Munoz de Cote

Papers from Dipyaman Banerjee's perspective

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

1. Markov Games as a Framework for Multi-Agent Reinforcement Learning
2. The Theory of Learning in Games
3. Reinforcement Learning: An Introduction
4. Correlated Q-Learning
5. The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
6. Nash Convergence of Gradient Dynamics in General-Sum Games
7. ImageNet classification with deep convolutional neural networks
8. Multiagent learning using a variable learning rate
9. Friend-or-Foe Q-learning in General-Sum Games
10. Asynchronous Methods for Deep Reinforcement Learning

Their papers

• Reaching pareto-optimality in prisoner’s dilemma using conditional joint action learning (2007) — 65 citations