Amico: An Event-Driven Modular Framework for Persistent and Embedded Autonomy

• URL: http://arxiv.org/abs/2507.14513v1
• Date: Sat, 19 Jul 2025 07:21:09 GMT
• Title: Amico: An Event-Driven Modular Framework for Persistent and Embedded Autonomy
• Authors: Hongyi Yang, Yue Pan, Jiayi Xu, Kelsen Liu,
• Abstract summary: We present Amico, a modular, event-driven framework for building autonomous agents optimized for embedded systems.<n>Amico supports reactive, persistent agents that operate efficiently across embedded platforms and browser environments via WebAssembly.
• Score: 7.117236435809274
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Recent advances in large language models (LLMs) and autonomous agents have enabled systems capable of performing complex tasks across domains such as human-computer interaction, planning, and web navigation. However, many existing frameworks struggle in real-world or resource-constrained environments due to their reliance on cloud-based computation, limited robustness in dynamic contexts, and lack of persistent autonomy and environmental awareness. We present Amico, a modular, event-driven framework for building autonomous agents optimized for embedded systems. Written in Rust for safety and performance, Amico supports reactive, persistent agents that operate efficiently across embedded platforms and browser environments via WebAssembly. It provides clean abstractions for event handling, state management, behavior execution, and integration with reasoning modules. Amico delivers a unified infrastructure for constructing resilient, interactive agents suitable for deployment in settings with limited compute and intermittent connectivity.

Related papers

• Agentic Web: Weaving the Next Web with AI Agents [109.13815627467514]
  The emergence of AI agents powered by large language models (LLMs) marks a pivotal shift toward the Agentic Web.<n>In this paradigm, agents interact directly with one another to plan, coordinate, and execute complex tasks on behalf of users.<n>We present a structured framework for understanding and building the Agentic Web.
  arXiv  Detail & Related papers  (2025-07-28T17:58:12Z)
• State and Memory is All You Need for Robust and Reliable AI Agents [29.259008600842517]
  Large language models (LLMs) have enabled powerful advances in natural language understanding and generation.<n>Yet their application to complex, real-world scientific remain limited by challenges in memory, planning, and tool integration.<n>Here, we introduce SciBORG, a modular agentic framework that allows LLM-based agents to autonomously plan, reason, and achieve robust and reliable domain-specific task execution.
  arXiv  Detail & Related papers  (2025-06-30T02:02:35Z)
• PyGemini: Unified Software Development towards Maritime Autonomy Systems [2.088373411826489]
  PyGemini builds on the legacy of Autoferry Gemini to unify maritime autonomy development.<n>The framework functions as a stand-alone application, cloud-based service, or embedded library.<n>We demonstrate its versatility through a suite of maritime tools.
  arXiv  Detail & Related papers  (2025-06-06T17:43:00Z)
• Internet of Agents: Fundamentals, Applications, and Challenges [66.44234034282421]
  We introduce the Internet of Agents (IoA) as a foundational framework that enables seamless interconnection, dynamic discovery, and collaborative orchestration among heterogeneous agents at scale.<n>We analyze the key operational enablers of IoA, including capability notification and discovery, adaptive communication protocols, dynamic task matching, consensus and conflict-resolution mechanisms, and incentive models.
  arXiv  Detail & Related papers  (2025-05-12T02:04:37Z)
• An LLM-enabled Multi-Agent Autonomous Mechatronics Design Framework [49.633199780510864]
  This work proposes a multi-agent autonomous mechatronics design framework, integrating expertise across mechanical design, optimization, electronics, and software engineering.<n> operating primarily through a language-driven workflow, the framework incorporates structured human feedback to ensure robust performance under real-world constraints.<n>A fully functional autonomous vessel was developed with optimized propulsion, cost-effective electronics, and advanced control.
  arXiv  Detail & Related papers  (2025-04-20T16:57:45Z)
• Agent models: Internalizing Chain-of-Action Generation into Reasoning models [15.954047804223379]
  We position emphLarge Agent Models (LAMs) that internalize the generation of emphChain-of-Action (CoA)<n>Our proposed AutoCoA framework combines supervised fine-tuning (SFT) and reinforcement learning (RL)<n>Main components include step-level action triggering, trajectory-level CoA, and an internal world model to reduce real-environment interaction costs.
  arXiv  Detail & Related papers  (2025-03-09T12:19:47Z)
• Asynchronous Tool Usage for Real-Time Agents [61.3041983544042]
  We introduce asynchronous AI agents capable of parallel processing and real-time tool-use. Our key contribution is an event-driven finite-state machine architecture for agent execution and prompting. This work presents both a conceptual framework and practical tools for creating AI agents capable of fluid, multitasking interactions.
  arXiv  Detail & Related papers  (2024-10-28T23:57:19Z)
• MOSS: Enabling Code-Driven Evolution and Context Management for AI Agents [7.4159044558995335]
  We introduce MOSS (llM-oriented Operating System Simulation), a novel framework that integrates code generation with a dynamic context management system. At its core, the framework employs an Inversion of Control container in conjunction with decorators to enforce the least knowledge principle. We show how this framework can enhance the efficiency and capabilities of agent development and highlight its advantages in moving towards Turing-complete agents.
  arXiv  Detail & Related papers  (2024-09-24T14:30:21Z)
• Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence [79.5316642687565]
  Existing multi-agent frameworks often struggle with integrating diverse capable third-party agents. We propose the Internet of Agents (IoA), a novel framework that addresses these limitations. IoA introduces an agent integration protocol, an instant-messaging-like architecture design, and dynamic mechanisms for agent teaming and conversation flow control.
  arXiv  Detail & Related papers  (2024-07-09T17:33:24Z)
• AgentScope: A Flexible yet Robust Multi-Agent Platform [66.64116117163755]
  AgentScope is a developer-centric multi-agent platform with message exchange as its core communication mechanism. The abundant syntactic tools, built-in agents and service functions, user-friendly interfaces for application demonstration and utility monitor, zero-code programming workstation, and automatic prompt tuning mechanism significantly lower the barriers to both development and deployment.
  arXiv  Detail & Related papers  (2024-02-21T04:11:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.