Tagged articles

multi-agent-rl

5 articles · Page 1 of 1

Jul 13, 2026 · Artificial Intelligence

Agentic RL in Taobao Live: From RLVR to Multi‑Agent Reinforcement Learning

The article details how Taobao Live upgraded its static workflow to a low‑latency Agentic architecture, applied AgentTuning distillation and RLVR to curb hallucinations, and introduced a Multi‑Agent RL framework that separates tool‑calling and reply generation, achieving significant gains in factual correctness, helpfulness, and overall performance.

Agentic RLLLMdigital human

0 likes · 23 min read

Agentic RL in Taobao Live: From RLVR to Multi‑Agent Reinforcement Learning

Data Party THU

Jun 14, 2026 · Artificial Intelligence

Understanding Large‑Model Reinforcement Learning: Algorithms, Frameworks, and Emerging Trends

This article surveys five years of large‑model reinforcement learning, detailing the evolution from PPO + RLHF to DPO and GRPO, comparing reward‑model‑based and verifiable‑reward approaches, discussing multi‑agent extensions, and evaluating open‑source frameworks for training LLM‑driven agents.

AI alignmentDPOGRPO

0 likes · 34 min read

Understanding Large‑Model Reinforcement Learning: Algorithms, Frameworks, and Emerging Trends

Data Party THU

Jun 5, 2026 · Artificial Intelligence

A 2026 Survey of LLM‑Focused RL: From PPO to DPO, GRPO, and Multi‑Agent RL

This article reviews the five‑year evolution of reinforcement‑learning techniques for large language models, comparing PPO, DPO, GRPO and emerging multi‑agent approaches, analyzing their reward signals, practical trade‑offs, and the open‑source frameworks that support them.

DPOGRPOLLM

0 likes · 34 min read

A 2026 Survey of LLM‑Focused RL: From PPO to DPO, GRPO, and Multi‑Agent RL

DeepHub IMBA

May 19, 2026 · Artificial Intelligence

A 2026 Survey of LLM‑Focused RL: From PPO to DPO, GRPO, and Multi‑Agent RL

The article reviews five years of LLM‑centric reinforcement learning, tracing the evolution from early Q‑learning to PPO, then to Direct Preference Optimization, Group Relative Policy Optimization, and finally multi‑agent RL, detailing each method’s mechanics, strengths, failure modes, practical considerations, and emerging open‑source toolchains.

DPOGRPOLLM alignment

0 likes · 33 min read

Bilibili Tech

Aug 30, 2022 · Artificial Intelligence

Neural MMO Massive AI Team Survival Challenge: Advances in Multi‑Agent Decision AI

The IJCAI‑2022 Neural MMO Massive AI Team Survival Challenge demonstrated that deep reinforcement‑learning agents can achieve sophisticated cooperation and competition among 128 agents in a large‑scale MMO‑style world, highlighting the growing focus on decision‑AI, the effectiveness of self‑play and CTDE, and the platform’s potential for future research into population‑level behavior, economics, and complex real‑world decision making.

AI competitionDecision AIMassive AI

0 likes · 11 min read

Neural MMO Massive AI Team Survival Challenge: Advances in Multi‑Agent Decision AI