Based Exploration

Based exploration, a crucial aspect of artificial intelligence and robotics, focuses on efficiently searching and mapping unknown environments or parameter spaces. Current research emphasizes developing novel algorithms, including those based on potential fields, Thompson sampling, and Bayesian optimization, to improve exploration speed, sample efficiency, and robustness in various settings, such as multi-robot systems and reinforcement learning. These advancements are significant for improving the autonomy and adaptability of robots in complex tasks, as well as accelerating the training of efficient AI agents in challenging domains.