Ho-fung Leung

Artificial Intelligence · 2003–2020

A researcher in the Science corpus: 3 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Reinforcement Learning — 14 citations into it

Whom Ho-fung Leung trusts overall

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

1. Ming Tan
2. Christopher J. C. H. Watkins
3. Caroline Claus
4. Laëtitia Matignon
5. Peter S. Dayan

Papers from Ho-fung Leung's perspective

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

1. Multi Agent Reinforcement Learning Independent vs Cooperative Agents
2. The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
3. Double Q-learning
4. Independent reinforcement learners in cooperative Markov games: a survey regarding coordination problems
5. Technical Note: Q-Learning
6. Cooperative Multi-agent Control Using Deep Reinforcement Learning
7. Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
8. Playing FPS Games with Deep Reinforcement Learning
9. Decisions with Multiple Objectives: Preferences and Value Trade-Offs
10. Teacher-Student Framework: a Reinforcement Learning Approach

Their papers

• A Q-values Sharing Framework for Multi-agent Reinforcement Learning under Budget Constraint (2020) — 10 citations
• A Q-values Sharing Framework for Multiple Independent Q-learners (2019) — 12 citations
• A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments (2003) — 340 citations