Marley Lee
Papers
1
Total Citations
6
H-Index
1
About
Marley Lee’s research lies at the intersection of artificial intelligence and robotics, with a focus on reinforcement learning and autonomous decision-making. In their most-cited work, “Robot Soccer Using Deep Q Network” (2018), Lee demonstrated how deep reinforcement learning can be applied to complex, real-time multi-agent environments, specifically within the RoboCup challenge. By adapting the Deep Q Network algorithm to four distinct soccer scenarios, Lee showed that RL agents could learn effective strategies for coordination, positioning, and ball control without explicit programming. Though the paper has garnered 6 citations, its significance lies in its early application of deep RL to a benchmark problem that continues to inspire research in embodied AI and multi-agent systems. Lee’s work contributes to a growing body of knowledge on how intelligent agents can learn from interaction in dynamic, adversarial settings. For students and researchers exploring reinforcement learning in robotics, Lee’s paper offers a clear, practical entry point into the challenges and possibilities of training agents for competitive, real-world-inspired tasks.
Research Focus
Key Achievements
Top Papers
- 1Robot Soccer Using Deep Q Network6 citations · 2018