Feint in Multi-Player Games

Junyu Liu, Wangkai Jin, XiangjunPeng

Status:

Under Review

Topic:

Machine Learning


Proposed, implemented and evaluated the high-level strategy formalization of Feint in Multi-Player Games. Comprehensively addressed the formalized Feint in terms of the temporal, spatial and collective impacts. Implemented the formalized Feint and strategies under the state-of-the-art progress of multi-agent modeling. The experiment results show that our formalization of Feint in Multi-Player Games can greatly improve the reward gains from the game and significantly improve the diversity of Multi-Player Games with only negligible overheads in terms of response time.