Combining Dense and Sparse Rewards to Improve Deep Reinforcement Learning Policies in Reach-Avoid Games with Faster Evaders in Two vs. One Scenarios. - Jefferson Silveira; Kalena McCloskey; Camille Alain Rabbath; Craig Williams; Sidney Givigi (CoDIT, 2024)