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Found 5 papers, 3 papers with code
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
In this work, we take an alternative approach and propose CtRL-Sim, a method that leverages return-conditioned offline reinforcement learning (RL) to efficiently generate reactive and controllable traffic agents.
Direct Behavior Specification via Constrained Reinforcement Learning
The standard formulation of Reinforcement Learning lacks a practical way of specifying what are admissible and forbidden behaviors.
Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
AutoBots can produce either the trajectory of one ego-agent or a distribution over the future trajectories for all agents in the scene.
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
In our endeavor to create a navigation assistant for the BVI, we found that existing Reinforcement Learning (RL) environments were unsuitable for the task.
A Survey of Mobile Computing for the Visually Impaired
The number of visually impaired or blind (VIB) people in the world is estimated at several hundred million.
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