28 citations · 64 across the 7 of their papers we have counts for
4 papers · 1 filter
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery
Jiachen Yang, Igor Borovikov, Hongyuan Zha
Human players in professional team sports achieve high level coordination by dynamically choosing complementary skills and executing primitive actions to perform these skills. As a…
On Multi-Agent Learning in Team Sports Games
Yunqi Zhao, Igor Borovikov, Jason Rupert +2
In recent years, reinforcement learning has been successful in solving video games from Atari to Star Craft II. However, the end-to-end model-free reinforcement learning (RL) is no…
Towards Interactive Training of Non-Player Characters in Video Games
Igor Borovikov, Jesse Harder, Michael Sadovsky +1
There is a high demand for high-quality Non-Player Characters (NPCs) in video games. Hand-crafting their behavior is a labor intensive and error prone engineering process with limi…
Winning Isn't Everything: Enhancing Game Development with Intelligent Agents
Yunqi Zhao, Igor Borovikov, Fernando de Mesentier Silva +14
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. In this paper, we study the problem of training intellige…