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An Autonomous Emotional Virtual Character: An Approach with Deep and Goal-Parameterized Reinforcement Learning
2020
Journal of Interactive Systems
We have developed an autonomous virtual character guided by emotions. The agent is a virtual character who lives in a three-dimensional maze world. We found that emotion drivers can induce the behavior of a trained agent. Our approach is a case of goal parameterized reinforcement learning. Thus, we create conditioning between emotion drivers and a set of goals that determine the behavioral profile of a virtual character. We train agents who can randomly assume these goals while trying to
doi:10.5753/jis.2020.751
fatcat:3pmme7d2k5ebjkazsxjvgzn3qe