Beyond Winning and Losing: Modeling Human Motivations and Behaviors with Vector-valued Inverse Reinforcement Learning

no code implementations • 27 Sep 2018 • Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng

In recent years, reinforcement learning methods have been applied to model gameplay with great success, achieving super-human performance in various environments, such as Atari, Go and Poker.

Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning

no code implementations • 1 Jul 2018 • Baoxiang Wang, Tongfang Sun, Xianjun Sam Zheng

Using the results of motivation modeling, we also predict and explain their diverse gameplay behaviors and provide a quantitative assessment of how the redesign of the game environment impacts players' behaviors.

reinforcement-learning Reinforcement Learning (RL)

A Computational Model of Afterimages based on Simultaneous and Successive Contrasts

no code implementations • 13 Sep 2017 • Jinhui Yu, Kailin Wu, Kang Zhang, Xianjun Sam Zheng

The colors of negative afterimages differ from the old stimulating colors in the original image when the color in the new area is either neutral or chromatic.