title: AgentScope: A Flexible yet Robust Multi-Agent Platform
summary: With the rapid advancement of Large Language Models (LLMs), significant
  progress has been made in multi-agent applications. However, the complexities
  in coordinating agents' cooperation and LLMs' erratic performance pose notable
  challenges in developing robust and efficient multi-agent applications. To
  tackle these challenges, we propose AgentScope, a developer-centric multi-agent
  platform with message exchange as its core communication mechanism. Together
  with abundant syntactic tools, built-in resources, and user-friendly
  interactions, our communication mechanism significantly reduces the barriers to
  both development and understanding. Towards robust and flexible multi-agent
  application, AgentScope provides both built-in and customizable fault tolerance
  mechanisms while it is also armed with system-level supports for multi-modal
  data generation, storage and transmission. Additionally, we design an
  actor-based distribution framework, enabling easy conversion between local and
  distributed deployments and automatic parallel optimization without extra
  effort. With these features, AgentScope empowers developers to build
  applications that fully realize the potential of intelligent agents. We have
  released AgentScope at https://github.com/modelscope/agentscope, and hope
  AgentScope invites wider participation and innovation in this fast-moving
  field.
paper_authors._id: 65d80ee62a17b13e8fdd3ac0
paper_authors.name: Dawei Gao
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paper_authors.name: Zitao Li
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paper_authors.name: Weirui Kuang
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paper_authors.fullname: weirui kuang
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paper_authors.user: rayrayray
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paper_authors.name: Xuchen Pan
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paper_authors.fullname: Xuchen Pan
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paper_authors.user: panxuchen
paper_authors._id: 65d80ee62a17b13e8fdd3ac4
paper_authors.name: Daoyuan Chen
paper_authors.status: admin_assigned
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paper_authors.fullname: Daoyuan Chen
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paper_authors.user: yxdyc
paper_authors._id: 65d80ee62a17b13e8fdd3ac5
paper_authors.name: Zhijian Ma
paper_authors._id: 65d80ee62a17b13e8fdd3ac6
paper_authors.name: Bingchen Qian
paper_authors._id: 65d80ee62a17b13e8fdd3ac7
paper_authors.name: Liuyi Yao
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-23T12:45:45.752Z
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paper_authors.fullname: Liuyi Yao
paper_authors.type: user
paper_authors.user: Briayao
paper_authors._id: 65d80ee62a17b13e8fdd3ac8
paper_authors.name: Lin Zhu
paper_authors._id: 65d80ee62a17b13e8fdd3ac9
paper_authors.name: Chen Cheng
paper_authors._id: 65d80ee62a17b13e8fdd3aca
paper_authors.name: Hongzhu Shi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-23T12:46:23.764Z
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paper_authors.fullname: Hongzhu Shi
paper_authors.type: user
paper_authors.user: vivianvolvo
paper_authors._id: 65d80ee62a17b13e8fdd3acb
paper_authors.name: Yaliang Li
paper_authors._id: 65d80ee62a17b13e8fdd3acc
paper_authors.name: Bolin Ding
paper_authors._id: 65d80ee62a17b13e8fdd3acd
paper_authors.name: Jingren Zhou
paper_authors.status: admin_assigned
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paper_title: AgentScope: A Flexible yet Robust Multi-Agent Platform
paper_summary: With the rapid advancement of Large Language Models (LLMs), significant
  progress has been made in multi-agent applications. However, the complexities
  in coordinating agents' cooperation and LLMs' erratic performance pose notable
  challenges in developing robust and efficient multi-agent applications. To
  tackle these challenges, we propose AgentScope, a developer-centric multi-agent
  platform with message exchange as its core communication mechanism. Together
  with abundant syntactic tools, built-in resources, and user-friendly
  interactions, our communication mechanism significantly reduces the barriers to
  both development and understanding. Towards robust and flexible multi-agent
  application, AgentScope provides both built-in and customizable fault tolerance
  mechanisms while it is also armed with system-level supports for multi-modal
  data generation, storage and transmission. Additionally, we design an
  actor-based distribution framework, enabling easy conversion between local and
  distributed deployments and automatic parallel optimization without extra
  effort. With these features, AgentScope empowers developers to build
  applications that fully realize the potential of intelligent agents. We have
  released AgentScope at https://github.com/modelscope/agentscope, and hope
  AgentScope invites wider participation and innovation in this fast-moving
  field.
paper_ai_keywords: Large Language Models (LLMs) multi-agent applications AgentScope message exchange syntactic tools user-friendly interactions multi-modal data generation storage and transmission actor-based distribution framework local and distributed deployments automatic parallel optimization intelligent agents