Guni Sharon
About
Assistant professor, Texas A&M University, Department of Computer Science & Engineering Research Interests: Artificial Intelligence, Intelligent transportation systems, Reinforcement learning, Combinatorial optimization Dr. Sharon has a strong theoretical basis in artificial intelligence. Specifically, reinforcement learning, combinatorial search, multiagent route assignment, game theory, flow and convex optimization, and multiagent modeling and simulation. He gained vast knowledge and experience in utilizing his theoretical foundations towards traffic management and traffic optimization application. Dr. Sharon strives to further the impact of his applicable expertise for solving real-life problems while simultaneously continuing to make theoretical advances that justify the proposed solutions.
Research Performance Summary
First Recorded Paper
Pruning techniques for the increasing cost tree search for optimal multi-agent pathfinding
Year: 2011
Citations: 23
Venue: Proceedings of the International Symposium on Combinatorial Search 2 (1
Latest Recorded Paper
Policy-Guided Search on Tree-of-Thoughts for Efficient Problem Solving with Bounded Language Model Queries
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2601.03606
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.