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Found 5 papers, 2 papers with code
Refined Policy Distillation: From VLA Generalists to RL Experts
Recent generalist Vision-Language-Action Models (VLAs) can perform a variety of tasks on real robots with remarkable generalization capabilities.
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks.
A Review of Safe Reinforcement Learning: Methods, Theory and Applications
To establish a good foundation for future safe RL research, in this paper, we provide a review of safe RL from the perspectives of methods, theories, and applications.
Towards Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network
As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment.
Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach
This model is the main focus of this work, as its contribution is not limited to engineering but also applicable to neuroscience.
