Evolutionary Curriculum

Evolutionary curriculum learning aims to improve the robustness and generalizability of artificial agents, particularly those trained using reinforcement learning, by dynamically adjusting the training environment's complexity. Current research focuses on developing algorithms that automatically generate increasingly challenging training curricula, often employing evolutionary methods to optimize both the agent's policy and the environment's difficulty. This approach addresses limitations of traditional reinforcement learning, such as poor generalization and vulnerability to unexpected situations, leading to more adaptable and reliable agents for applications in robotics, game AI, and other domains requiring robust decision-making.