Very Large-Scale Multi-Agent Simulation in AgentScope
Xuchen Pan Affiliation: Alibaba Group Dawei Gao Affiliation: Alibaba Group Yuexiang Xie Affiliation: Alibaba Group Yushuo Chen Affiliation: Alibaba Group Zhewei Wei Affiliation: Renmin University of China Yaliang Li Affiliation: Alibaba Group Bolin Ding Affiliation: Alibaba Group Ji-Rong Wen Affiliation: Renmin University of China Jingren Zhou Affiliation: Alibaba Group
Abstract
Recent advances in large language models (LLMs) have opened new avenues for applying multi-agent systems in very large-scale simulations. However, there remain several challenges when conducting multi-agent simulations with existing platforms, such as limited scalability and low efficiency, unsatisfied agent diversity, and effort-intensive management processes. To address these challenges, we develop several new features and components for AgentScope, a user-friendly multi-agent platform, enhancing its convenience and flexibility for supporting very large-scale multi-agent simulations. Specifically, we propose an actor-based distributed mechanism as the underlying technological infrastructure towards great scalability and high efficiency, and provide flexible environment support for simulating various real-world scenarios, which enables parallel execution of multiple agents, automatic workflow conversion for distributed deployment, and both inter-agent and agent-environment interactions. Moreover, we integrate an easy-to-use configurable tool and an automatic background generation pipeline in AgentScope, simplifying the process of creating agents with diverse yet detailed backgroun
原文 arXiv:2407.17789;中英对照 + 大白话阅读 https://aha.fim.ai/paper/2407.17789v2