PPO (Proximal Policy Optimization), a classic algorithm that was later widely used in RLHF and large model training, was rejected by NIPS 2017 back then. This matter was recently brought up by John ...
Abstract: In this paper, we propose KL-Beyond-Clip PPO (KLBC-PPO), a novel algorithm derived from PPO, designed to offer a more efficient policy update mechanism. The PPO-Clip algorithm limits the ...
elevator-ai/ ├── environment/ │ ├── building.py # Core simulation entities │ ├── elevator_env.py # Gymnasium environment │ └── traffic_patterns.py # Probabilistic passenger spawning ├── agents/ │ ├── ...
This repository provides an implementation of the Proximal Policy Optimization (PPO) algorithm for training an agent to master the CarRacing-v3 environment from OpenAI Gym with StableBaselines3. It ...
Parallel hybrid vehicles face challenges in real-time torque distribution, including slow feedback speeds and suboptimal energy allocation, which constrain overall energy efficiency. This study aims ...
Following the 2024 U.S. presidential election, millions of aggravated X users flocked to Bluesky to avoid the partisan vitriol that had overtaken the older social media platform. Designed without an ...
LLMs have gained outstanding reasoning capabilities through reinforcement learning (RL) on correctness rewards. Modern RL algorithms for LLMs, including GRPO, VinePPO, and Leave-one-out PPO, have ...
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