Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
Abstract: This article studies the pursuit–evasion game involving nonholonomic vehicles constrained by input saturation, aiming for the pursuer to intercept an evasive opponent. Unlike the previous ...
verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...
Meet NVIDIA Nitrogen, a generalist gaming agent trained on 40,000 hours of video, so you can understand how imitation learning scales.
Nemotron-3 Nano (available now): A highly efficient and accurate model. Though it’s a 30 billion-parameter model, only 3 billion parameters are active at any time, allowing it to fit onto smaller form ...
AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
Abstract: In 3 vs. 3 online basketball games, finite state machine (FSM)-based Game artificial intelligence (AI) has traditionally been employed. However, limitations such as repetitive behavior ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback