Search Results for author:
Found 6 papers, 2 papers with code
From Words to Routes: Applying Large Language Models to Vehicle Routing
The success of LLMs in these tasks leads us to wonder: What is the ability of LLMs to solve vehicle routing problems (VRPs) with natural language task descriptions?
Guaranteed Trust Region Optimization via Two-Phase KL Penalization
Then, we show that introducing a "fixup" phase is sufficient to guarantee a trust region is enforced on every policy update while adding fewer than 5% additional gradient steps in practice.
HyperPPO: A scalable method for finding small policies for robotic control
We demonstrate that the neural policies estimated by HyperPPO are capable of decentralized control of a Crazyflie2. 1 quadrotor.
Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning
In this work, we propose an end-to-end DRL approach to control quadrotor swarms in environments with obstacles.
QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control
In addition to speed, such simulators need to model the physics of the robots and their interaction with the environment to a level acceptable for transferring policies learned in simulation to reality.
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
In this work we aim to solve this problem by optimizing the efficiency and resource utilization of reinforcement learning algorithms instead of relying on distributed computation.
