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- Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Large Language Models (LLMs) have shown remarkable capabilities in natural language tasks requiring complex reasoning, yet their application in agentic, multi-step reasoning within interactive environments remains a difficult challenge Traditional supervised pre-training on static datasets falls short in enabling autonomous agent capabilities needed to perform complex decision-making in
- GitHub - sentient-engineering agent-q: agent q - oss advanced reasoning . . .
About agent q - oss advanced reasoning and learning for autonomous ai agents Readme MIT license
- MultiOn introduces a new autonomous AI agent, Agent Q, similar to Q . . .
MultiOn introduces a new type of autonomous AI agent, Agent Q Agent Q is a self-supervised agent reasoning and search framework that can autonomously improve in real environments through self-play and reinforcement learning Agent Q is a new self-supervised agent reasoning and search framework, officially released after six months of development
- Advanced Learning for Autonomous Agents — A Dive into “Agent Q”
The Agent Q framework represents a significant leap forward in autonomous decision-making for AI agents By incorporating Monte Carlo Tree Search, self-critique, and Direct Preference Optimization, it enhances the ability of LLMs to perform complex, real-world tasks that require multiple steps and real-time adaptation
- Agent Q: Advancing AI Autonomy in Dynamic Environments
Discover the potential of Agent Q, a novel AI framework that aims to make AI models more autonomous in interacting with dynamic environments like websites
- Agent Q – MultiOn公司推出的AI智能体，可以自我学习进化
Agent Q是MultiOn公司联合斯坦福大学推出的自监督代理推理和搜索框架。Agent Q融合了引导式蒙特卡洛树搜索（MCTS）、AI自我批评和直接偏好优化（DPO）等技术，使AI模型能通过迭代微调和基于人类反馈的强化学习进行自我改进。
- AgentQ, An Above-Human Agent | Medium
MultiOn has announced a new agent, AgentQ, a jaw-dropping product that consolidates much of what I’ve been discussing for a while now: combining LLMs with search But this agent is special
- Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
We believe this represents a substantial leap forward in the capabilities of autonomous agents, paving the way for more sophisticated and reliable decision-making in real-world settings
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