Abstract
2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on robotics are presented i n a new report. According to news reporting originating from the University of M iskolc by NewsRx correspondents, research stated, "Using reinforcement learning to generate the collective behavior of swarm robots is a common approach." Our news journalists obtained a quote from the research from University of Misko lc: "Yet, formulating an appropriate reward function that aligns with specific o bjectives remains a significant challenge, particularly as the complexity of tas ks increases. In this paper, we develop a deep inverse reinforcement learning mo del to uncover the reward structures that guide autonomous robots in achieving t asks by demonstrations. Deep inverse reinforcement learning models are particula rly well-suited for complex and dynamic environments where predefined reward fun ctions may be difficult to specify. Our model can generate different collective behaviors according to the required objectives and effectively copes with contin uous state and action spaces, ensuring a nuanced recovery of reward structures. We tested the model using E-puck robots in the Webots simulator to solve two tas ks: searching for dispersed boxes and navigation to a predefined position. Recei ving rewards depends on demonstrations collected by an intelligent pre-trained s warm using reinforcement learning act as an expert."
NETL
NSTL