Hierarchical multi agent. Each agent can represent an autonomous entity capable of making decisions and Mar 9, 2025 · In a hierarchical multi-agent system, specialized agents operate under the coordination of a central supervisor agent. TAO advances beyond human-in-the-loop methods by deploying specialized LLM agent tiers for autonomous AI oversight, featuring complexity-adaptive checks and dynamic routing. hi′er·ar′chi·cal·ly adv. . Aug 21, 2024 · Recent advancements in reinforcement learning have made significant impacts across various domains, yet they often struggle in complex multi-agent environments due to issues like algorithm instability, low sampling efficiency, and the challenges of exploration and dimensionality explosion. LangGraph provides a robust and flexible framework for building HMAS, allowing you to manage state, define complex control flows, and orchestrate the interactions between agents at different Multi-agent systems often face challenges such as elevated communication demands and intricate interactions. Apr 4, 2006 · In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. The intelligent game has made great achievements while also posing grand challenges to reinforcement learning such as multi-agent coordination, long time horizons, complex action control, sparse rewards, etc. Jun 14, 2025 · Recent advances in agent systems based on large language models (LLMs) have demonstrated strong capabilities in solving complex tasks. But what happens when the complexity really scales? This is where hierarchical multi-agent systems (HMAS) come into play. While single-agent systems have their limitations, multi-agent systems (MAS) offer a powerful approach by distributing the workload and enabling collaboration. We introduce \\projectname, a hierarchical multi-agent framework for general-purpose task solving that integrates Jan 6, 2025 · Hierarchical multi-agent systems are structured environments in which multiple agents work together under a well-defined chain of command, often supervised by a central entity. They divide labor among specialized agents while ensuring that their activities are synchronized to achieve broader objectives. However, classic non-hierarchical MARL algorithms still cannot address various complex multi-agent problems that require hierarchical cooperative behaviors. In Sep 21, 2023 · To address these challenges, we present Hierarchical Multi-Agent Skill Discovery (HMASD), a two-level hierarchical algorithm for discovering both team and individual skills in MARL. However, existing solutions to the control and coordination of UAV s are mostly limited to specific environments and are not robust to handle unreliable/unstable communications. Applying deep Hierarchical Agent Teams In our previous example (Agent Supervisor), we introduced the concept of a single supervisor node to route work between different worker nodes. " Mar 26, 2024 · Multi-Agent Reinforcement Learning (MARL) has been successful in solving many cooperative challenges. This model leverages a central “master” agent to guide the overall strategy, while subordinate agents focus on executing specific tasks. We present KG4Diagnosis, a novel hierarchical multi-agent framework that combines LLMs with automated knowledge graph construction, encompassing 362 common diseases across medical specialties. In this algorithm, we add a communication level to the hierarchical decomposition of the problem below each cooperation level. A Lyapunov function is introduce This article investigates the problem of real-time task assignment with heterogeneous agents while considering resource constraints. A hierarchical reinforcement learning-based(HRL) method to address the problem has been proposed. To address this, we introduce AgentSafe, a novel framework that enhances MAS security through hierarchical information management and memory protection. How to use hierarchical in a sentence. The objective is to identify effective Courses of Action that lead to mission success within preset simulations, thereby enabling the exploration of real-world defense scenarios at low cost and in a safe-to-fail setting. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more. Hierarchical definition: of, belonging to, or characteristic of a hierarchy. A hierarchical system or organization is one in which people have different ranks or positions, depending on how important they are. Of or relating to a hierarchy. May 13, 2025 · This work presents a Hierarchical Multi-Agent Reinforcement Learning framework for analyzing simulated air combat scenarios involving heterogeneous agents. In these systems, higher-level agents manage broader goals and delegate subtasks to lower-level agents, creating a tree-like hierarchy. AgentSafe classifies information by Dec 22, 2024 · Integrating Large Language Models (LLMs) in healthcare diagnosis demands systematic frameworks that can handle complex medical scenarios while maintaining specialized expertise. First, the complexity of coordinating multiple agents increases computation overhead and can slow down the debugging process, particularly in resource-constrained environments. Let’s explore these systems, why they are necessary, the frameworks that support them Jul 29, 2024 · A multi-agent system helps us separate the workflows, thus making it easier to find faults/debugging and also explicitly define the interactions between different components. The cooperative knowledge and policies learned in non-hierarchical algorithms are implicit and not interpretable, thereby restricting the In the current multi-UAV adversarial games, issues exist such as the instability and difficulty in learning distributed strategies, as well as a lack of coordinated formation UAVs. arranged according to people's or things' level of importance, or relating to such a system: 2…. This chapter explores patterns for multi-agent workflows through hierarchical task delegation, parallel execution, and intelligent resource management. Jul 3, 2025 · hierarchical (not comparable) Pertaining to a hierarchy. the traditional hierarchical system of military organization. Learn more. Aug 21, 2024 · This paper seeks to integrate the proposed hierarchical architecture with established multi-agent reinforcement learning strategies to formulate a comprehensive GMAH algorithm, thereby extending the advantages of hierarchical designs to the multi-agent context. Jul 11, 2024 · In multi-agent reinforcement learning (MARL), the Centralized Training with Decentralized Execution (CTDE) framework is pivotal but struggles due to a gap: global state guidance in training versus reliance on local observations in execution, lacking global signals. Dec 5, 2024 · View a PDF of the paper titled Hierarchical Multi-Agent DRL Based Dynamic Cluster Reconfiguration for UAV Mobility Management, by Irshad A. Hierarchical links can extend "vertically" upwards or downwards via multiple links in the same direction, following a path. Feb 12, 2025 · Hierarchical Multi-Agent Systems represent a powerful approach to tackling complex problems by breaking them down into smaller, more manageable tasks. All parts of the hierarchy that are not linked vertically to one another nevertheless can be "horizontally" linked through a path by traveling up the hierarchy to find a common direct or indirect superior, and then down again. However, conventional rule-based methods employed by public Mar 16, 2025 · In many multi-agent systems, a hierarchical structure known as the master-subordinate model is employed to further refine coordination and task delegation. We introduce a hierarchical multi-agent reinforcement learning (RL) framework, and propose a hierarchical multi-agent RL algorithm called Cooperative HRL. This supervisor controls all communication flow and task delegation, making intelligent decisions about which agent to invoke based on the current context and requirements. In this paper, we propose a hierarchical architecture learning paradigm that methodologically combines the multi-agent algorithm and single-agent algorithm in multi-agent environments Jul 10, 2024 · We propose multi-horizon Monte Carlo tree search (MH-MCTS), the first framework for integrated hierarchical multi-horizon, multi-agent planning based on Monte Carlo tree search (MCTS). 'hierarchical' also found in these entries (note: many are not synonyms or translations): Hierarchical links can extend "vertically" upwards or downwards via multiple links in the same direction, following a path. Therefore, efficient strategies for medical resource allocation are urgently needed. Mar 6, 2025 · Large Language Model based multi-agent systems are revolutionizing autonomous communication and collaboration, yet they remain vulnerable to security threats like unauthorized access and data breaches. We propose a hierarchical multi-agent reinforcement learning framework with three levels of control. May 29, 2023 · Unmanned Aerial Vehicles (UAVs) have become prevalent in Search-And-Rescue (SAR) missions. HIERARCHICAL definition: 1. In Sep 4, 2024 · Multi-Agent Reinforcement Learning (MARL) has been successful in solving many cooperative challenges. In these systems, agents are typically organized at different levels, with higher-level agents having more responsibilities and oversight compared to lower-level agents. To address these challenges, we present Hierarchical Multi-Agent Skill Discovery (HMASD), a two-level hierarchical algorithm for discovering both team and individual skills in MARL. Feb 23, 2024 · "Hierarchal" and "hierarchical" both relate to hierarchy, but "hierarchical" is more commonly used to describe structures or systems with ranked positions. This framework integrates three types of Sep 1, 2006 · In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. meanings, etymology, pronunciation and more in the Oxford English Dictionary hi′er•ar′chi•cal•ly, adv. We propose an innovative hierarchical graph attention actor-critic reinforcement learning method to address the issues, which uses the hierarchical graph attention to capture the relationships of cooperation or competition among agents, and the agent enables a better understand of the Hierarchical multi-agent systems (HMAS) are decentralized AI architectures where agents are organized into layered structures to coordinate complex tasks. However, most current methods lack mechanisms for coordinating specialized agents and have limited ability to generalize to new or diverse domains. The method employs multiple simultaneous MCTS optimisations for each planning level within each agent, which are designed to optimise a joint objective function. With the advent of the COVID-19 pandemic, the shortage in medical resources became increasingly more evident. Hierarchical reinforcement learning (HRL) offers a structured approach to decompose complex tasks into Jan 23, 2024 · How are those agents connected? An agent supervisor is responsible for routing to individual agents. We extend the multi-agent HRL framework to include communication decisions and propose a coop-erative multi-agent HRL algorithm called COM-Cooperative HRL. Our framework mirrors We propose novel hierarchical multi-agent reinforcement learning (MARL) strategies to train multiple blue agents tasked with protecting a network against red agents. We introduce a hierarchical multi-agent reinforcement learning (RL) framework, and propose a hierarchical We extend the multi-agent HRL framework to include communication decisions and propose a coop-erative multi-agent HRL algorithm called COM-Cooperative HRL. To deal with these challenges, Hierarchical Multi-Agent Actor-Critic (HMAAC) framework is proposed where a high-level policy is This paper tackles the task of obstacle-aware, long-horizon pushing by multiple quadrupedal robots. Unlike most existing studies, the method is to assign the tasks to agents such that the resource consumption is minimized while respecting the resource constraints Hierarchical multi-agent systems (HMAS) are frameworks where multiple agents operate within a structured hierarchy to achieve common goals or tasks. In this way, the supervisor can also be thought of an agent whose tools are other agents! Hierarchical Agent Teams Examples: Python JS This is similar to the above example, but now the agents in the nodes are actually other langgraph objects Feb 1, 2016 · This study studies the exponential state consensus problem for hierarchical multi-agent dynamical systems with switching topology and inter-layer communication delay. In response, we propose a novel hierarchical heterogeneous multi-agent (HHMA) framework designed for underwater search scenarios. The Need for Multi-Agent Systems Consider a typical enterprise feature request: "Add user analytics tracking across our web app, mobile app, and backend services. You can do this by Dec 2, 2024 · To address this challenge, this paper proposes the HMSC-LLMs method, a novel hierarchical multi-agent service composition algorithm based on LLMs, to better interact with users through prompts. Inspired by human societal consensus mechanisms, we introduce the Hierarchical Consensus-based Multi-Agent Reinforcement Learning Apr 13, 2025 · We present HM-RAG, a novel Hierarchical Multi-agent Multimodal RAG framework that pioneers collaborative intelligence for dynamic knowledge synthesis across structured, unstructured, and graph-based data. But what if the job for a single worker becomes too complex? What if the number of workers becomes too large? For some applications, the system may be more effective if work is distributed hierarchically. The cooperative knowledge and policies learned in non-hierarchical algorithms are implicit and not interpretable, thereby restricting the Feb 6, 2025 · Large Language Model (LLM)-empowered multi-agent systems extend the cognitive boundaries of individual agents through disciplined collaboration and interaction, while constructing these systems often requires labor-intensive manual designs. Oct 23, 2024 · While our study introduces the end-to-end framework FixAgent with a hierarchical multi-agent approach for debugging, it does come with certain limitations. American Heritage® Dictionary of the English Language, Fifth Definition of hierarchical adjective in Oxford Advanced Learner's Dictionary. Despite extensive research, research gaps remain in multi-agent scenarios, particularly for automatically extracting subgroup coordination patterns in a multi-agent task. In this framework, agents are cooperative and homogeneous (use the same task decomposition Marine target searching is a complex task due to large search areas, unique signal propagation characteristics, and limited visibility, posing significant challenges for single-agent or homogeneous multi-agent systems. Meer and 5 other authors May 26, 2024 · Skills are effective temporal abstractions established for sequential decision making, which enable efficient hierarchical learning for long-horizon tasks and facilitate multi-task learning through their transferability. See examples of HIERARCHICAL used in a sentence. The meaning of HIERARCHICAL is of, relating to, or arranged in a hierarchy. However, these models often face constraints related to the number of agents or levels of hierarchies. This paper introduces Tiered Agentic Oversight (TAO), a hierarchical multi-agent framework enhanc-ing healthcare AI safety by emulating clinical hierarchies. Of or pertaining to an ecclesiastic or priestly order. American Heritage® Dictionary of the English Language, Fifth hierarchical, adj. Oct 15, 2024 · Hierarchical multi-agent models offer a promising solution by organizing agents into different levels, effectively addressing tasks with varying planning horizons. Classified or arranged according to various criteria into successive ranks or grades. Despite the availability of methods to automate the design of agentic workflows, they typically seek to identify a static, complex, one-size-fits-all The meaning of HIERARCHICAL is of, relating to, or arranged in a hierarchy. Feb 12, 2025 · The world is complex, and solving complex problems often requires coordinating multiple specialized agents. In this paper, a hierarchical multi-agent training framework is proposed to solve these problems, which categorizes UAV formations into two types of intelligent agents: virtual centroid agents and UAVs within the Hierarchical multi-agent systems (HMAS) are decentralized AI architectures where agents are organized into layered structures to coordinate complex tasks. Nov 27, 2024 · The HMSC-LLMs method adopts a hierarchical multi-agent mechanism, effectively reducing the number of candidate services in each large model and significantly alleviating the pathological issues in large models; HMSC-LLMs fully utilize the advantages of multiple LLMs to jointly make service composition decisions. eygfj iszv njdjzb mvkbp psbe brks noe ptsrro eygpp osrf
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