Peter Stone

A new framework enhances efficiency in multi-robot coordination and task execution.

Robots can better adapt to new terrains by predicting operator preferences.

Using game theory, robots coordinate movements in narrow areas to avoid collisions.

Robots adapt to diverse terrains using self-collected data.

t-DGR offers a new approach to continual learning, improving task retention and performance.

A novel teleoperation system simplifies robot training through real-time human control.

Exploration is key for effectively training agents in multitask reinforcement learning.

A new platform where robots learn complex tasks via air hockey.

Imitation learning helps robots move better in busy environments.

New AI program beats human drivers using only internal car data.

A new method improves robot learning efficiency through better human interaction.

Teams showcased their robot navigation skills in a challenging competition.

A new approach to state-space models enhances efficiency and performance in language tasks.

Enhancing robots' ability to adapt and learn from experiences.

A new method enhances robot training by aligning simulated tasks with real-world scenarios.

A new approach for faster computer learning in various tasks.

Researchers teach AI to understand simple commands for real-world actions.

Discover how reinforcement learning is transforming robot soccer.