Researchers have developed a novel method for training agents using both labeled actions and unlabeled trajectories, significantly reducing the need for costly and time-consuming data annotation.
New modeling reveals how future telescopes might detect key atmospheric gases indicative of life on Earth-like exoplanets.
Researchers have developed a new reinforcement learning framework that moves beyond optimizing for a single goal, enabling agents to better navigate complex scenarios and exhibit more nuanced behaviors.
Researchers are developing conversational agents that move beyond simple question-and-answer interactions to assess student well-being and tailor learning experiences accordingly.
New research reveals how decentralized AI agents can develop collective intelligence by balancing individual experience with communication through shared environmental cues.
Researchers have developed a new approach to coordinating multiple robots or agents, ensuring both collision avoidance and optimized area coverage.
A new framework combines the power of artificial intelligence with established medical expertise to create more reliable and interpretable image analysis.
Researchers have developed a novel under-actuated robotic finger that achieves robust grasping and manipulation with a simplified tendon routing system.
This review explores how high-energy radiation shapes the molecular landscape of the interstellar medium, driving chemical reactions in gas and ice.
New research combines reinforcement learning with a contextual reward system to significantly improve the reliability and adaptability of robotic grasping in complex scenarios.