Standard Interface
Standard interfaces are crucial for facilitating seamless interaction between humans, robots, and AI systems, aiming to improve efficiency, usability, and interoperability across diverse applications. Current research focuses on developing intuitive and adaptable interfaces, including those leveraging spiking neural networks for efficient temporal data processing, and employing machine learning to optimize information transfer and personalize interactions. These advancements are significant for accelerating research in fields like robotics, human-computer interaction, and AI, leading to more effective and user-friendly technologies in various sectors.
Papers
Gymnasium: A Standard Interface for Reinforcement Learning Environments
Mark Towers, Ariel Kwiatkowski, Jordan Terry, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Andreas Kallinteris, Markus Krimmel, Arjun KG, Rodrigo Perez-Vicente, Andrea Pierré, Sander Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis
Collaboration Between Robots, Interfaces and Humans: Practice-Based and Audience Perspectives
Anna Savery, Richard Savery