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Found 5 papers, 3 papers with code
Distributed multi-agent target search and tracking with Gaussian process and reinforcement learning
Deploying multiple robots for target search and tracking has many practical applications, yet the challenge of planning over unknown or partially known targets remains difficult to address.
Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
While reinforcement learning (RL) has achieved great success in acquiring complex skills solely from environmental interactions, it assumes that resets to the initial state are readily available at the end of each episode.
DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning
Hierarchical Reinforcement Learning (HRL) has made notable progress in complex control tasks by leveraging temporal abstraction.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
Unsupervised Reinforcement Learning for Transferable Manipulation Skill Discovery
Current reinforcement learning (RL) in robotics often experiences difficulty in generalizing to new downstream tasks due to the innate task-specific training paradigm.
Automating Reinforcement Learning with Example-based Resets
Deep reinforcement learning has enabled robots to learn motor skills from environmental interactions with minimal to no prior knowledge.
