News

s3: The new RAG framework that trains search agents with minimal data
S3 decouples RAG search from generation, boosting efficiency and generalization for enterprise LLM applications with minimal data.
IEEE1mon
Multi-Agent Reinforcement Learning for Collision Avoidance and Path Following of Autonomous Surface Vehicles
This paper presents a novel approach to tackling these challenges using Multi-agent Reinforcement Learning (MARL) for decentralized ... and other supporting Python libraries, offering a scalable and ...
marktechpost4mon
Kimi k1.5: A Next Generation Multi-Modal LLM Trained with Reinforcement Learning on Advancing AI with Scalable Multimodal Reasoning and Benchmark Excellence
Reinforcement learning (RL) has fundamentally transformed AI by ... In this tutorial, we will discover how to harness the power of an advanced AI Agent, augmented with both Python execution and result ...
GitHub10mon
Trackmania AI - Reinforcement Learning Agent
This repository contains code for training a reinforcement learning (RL) agent to drive autonomously ... a third-party tool that facilitates real-time communication between the Python-based AI agent ...
GitHub10mon
Reinforcement Learning in Python
"Reinforcement Learning Algorithms in Global Path Planning for Mobile ... Looking at the values of the table we can see the decision for the next action made by agent (mobile robot). The sequence of ...
IEEE1y
Multi-Agent and Multi-Target Reinforcement Learning for Satellite Sensor Tasking
This complexity underscores the importance of researching effective sensor tasking methods, a challenge ideally suited for Reinforcement Learning (RL ... effective use of RL in multi-agent systems, we ...
Frontiers1y
Neurorobotic reinforcement learning for domains with parametrical uncertainty
In this study, we used the neurorobotics platform (NRP) simulation framework to implement spiking reinforcement learning ... A video of the trained agent can be found in the Supplementary material ...