The former is concerned with techniques for decomposing either the problem to be solved or the collective behavior into simpler independent components that can be more easily handled by the learning process.Liviu A. PanaitSean LukeL. Panait, S. Luke, Collaborative multi-agent learning: A survey...
Multi-Agent Collaborative Learning Architecture, an improvement of about 6.5% over the best results achieved by Kansas Geological Survey with the same data ... CM Gifford - 《Proquest Llc》 被引量: 17发表: 2009年 Collective machine learning: Team learning and classification in multi-agent systems...
MASCE is to assist teaching and learning process and also to encourage collaborative learning among peers. This system shall be used in a blended learning environment as a supplement to the face-to-face lecture where students can use the system in the lab or from home after attending the ...
我们的框架通过智能代理之间的协作和知识交流,为提高LLM的能力和性能提供了途径。 In this paper, we present a novel framework for enhancing the capabilities of large language models (LLMs) by leveraging the power of multi-agent systems. Our framework introduces a collaborative environment where multiple ...
CAMPHOR: Collaborative Agents for Multi-Input Planning and High-Order Reasoning On Device While server-side Large Language Models (LLMs) demonstrate proficiency in tool integration and complex reasoning, deploying Small Language Models (SLMs) directly on devices brings opportunities to improve latency an...
Moreover, most of the prior research where agents are actually able to learn and adapt based on their past interactions mainly focuses on reinforcement learning techniques at the individual agent level. We argue that, in many important applications and contexts, complex large-scale collaborative ...
【LLM】GameGPT:游戏开发的多agent协作框架 (GameGPT: Multi-agent Collaborative Framework for Game Development) 无影寺 互联网行业 从业人员 5 人赞同了该文章 AI+游戏的现状 人工智能在游戏开发中的应用可以追溯到"星际争霸"(Starcraft)和"暗黑破坏神"等经典游戏。开发者一直需要AI系统来创建交互式虚拟...
Shum, H.P., Komura, T., Yamazaki, S.: Simulating multiple character interactions with collaborative and adversarial goals. IEEE Trans. Vis. Comput. Gr. 18(5), 741–752 (2010) Article Google Scholar Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A...
Online question-and-answer (Q\&A) systems based on the Large Language Model (LLM) have progressively diverged from recreational to professional use. This paper proposed a Multi-Agent framework with environmentally reinforcement learning (E-RL) for code correction called Code Learning (Co-Learning) ...
Co-Learning (ERNIE 4.0) 337 60 31 29 245 137.5 65.09 Co-Learning (Llama 3-8b) 317 81 32 21 251 112.8 64.24 Co-Learning (Spark V3) 319 48 14 4 317 57.7 54.84 Co-Learning (E-RL) 280 104 65 27 226 99.8 67.80Results in Papers With Code (↓ scroll down to see all results) He...