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Conference Paper ReAcTree: Hierarchical LLM Agent Trees with Control Flow for Long-Horizon Task Planning
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Authors
Jae-Woo Choi, Hyungmin Kim, Hyobin Ong, Youngwoo Yoon, Minsu Jang, Dohyung Kim, Jaehong Kim
Issue Date
2026-05
Citation
International Conference on Autonomous Agents and Multi-agent Systems (AAMAS) 2026, pp.319-328
Publisher
ACM
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.65109/UCGT7089
Abstract
Recent advancements in large language models (LLMs) have enabled significant progress in decision-making and task planning for embodied autonomous agents. However, most existing methods struggle with complex, long-horizon tasks because they rely on a monolithic trajectory that entangles all past decisions and observations to solve the entire task in a single unified process. To address this limitation, we propose ReAcTree, a hierarchical task-planning method that decomposes a complex goal into manageable subgoals within a dynamically constructed agent tree. Each subgoal is handled by an LLM agent node capable of reasoning, acting, and further expanding the tree, while control flow nodes coordinate the execution strategies of agent nodes. In addition, we integrate two complementary memory systems: each agent node retrieves goal-specific, subgoal-level examples from episodic memory and shares environment-specific observations through working memory. Experiments on the WAH-NL and ALFRED show ReAcTree consistently outperforms strong task-planning baselines such as ReAct across diverse LLMs. Notably, on WAH-NL, ReAcTree achieves a 61% goal success rate with Qwen 2.5 72B, nearly doubling ReAct’s 31%. The code is available at https://github.com/Choi-JaeWoo/ReAcTree.git.
Keyword
Hierarchical Task Planning, LLM Agents, Behavior Trees
KSP Keywords
Agent nodes, Behavior tree, Control flow, Decision-making, Execution strategies, Language Models, Memory System, Planning method, Success rate, Unified process, Working memory
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
CC BY