An Emotional Virtual Character: A Deep Learning Approach with Reinforcement Learning - Gomes, Gilzamir; Vidal, Creto; Cavalcante-Neto, Joaquim; Nogueira, Yuri (Anais do Simpósio de Realidade Virtual e Aumentada (SVR), 2019)
We have developed an emotional agent based on reinforcement learning. The agent is a virtual character who lives in a three-dimensional maze world. Thus, we found that an emotional engine can induce the behavior of an agent after training. The training algorithm was the Asynchronous Advantage Actor-Critic (A3C). Experiments showed that the emotional engine and reinforcement learning produced coherent behaviors. This is an important step towards believable autonomous virtual characters.