Robust and Efficient Tool Orchestration via Layered Execution Structures with Reflective Correction
🤖 AI Summary
Existing intelligent agents often suffer from high system fragility and substantial execution overhead in multi-tool coordination due to inadequate scheduling mechanisms. This work proposes a hierarchical orchestration paradigm that obviates the need for fine-grained dependency graphs by providing coarse-grained global guidance, coupled with context-constrained intra-layer execution. A pattern-aware local reflection mechanism is introduced to enable runtime error detection and repair without triggering costly global replanning. The approach significantly enhances the robustness of tool invocation while reducing execution complexity and resource consumption, yielding a lightweight and reusable tool orchestration component.
Application Category
📝 Abstract
Tool invocation is a core capability of agentic systems, yet failures often arise not from individual tool calls but from how multiple tools are organized and executed together. Existing approaches tightly couple tool execution with stepwise language reasoning or explicit planning, leading to brittle behavior and high execution overhead. To overcome these limitations, we revisit tool invocation from the perspective of tool orchestration. Our key insight is that effective orchestration does not require precise dependency graphs or fine-grained planning. Instead, a coarse-grained layer structure suffices to provide global guidance, while execution-time errors can be corrected locally. Specifically, we model tool orchestration as learning a layered execution structure that captures high-level tool dependencies, inducing layer-wise execution through context constraints. To handle execution-time failures, we introduce a schema-aware reflective correction mechanism that detects and repairs errors locally. This design confines errors to individual tool calls and avoids re-planning entire execution trajectories. This structured execution paradigm enables a lightweight and reusable orchestration component for agentic systems. Experimental results show that our approach achieves robust tool execution while reducing execution complexity and overhead. Code will be made publicly available.
Problem
Research questions and friction points this paper is trying to address.
tool orchestration
agentic systems
execution robustness
tool invocation
execution overhead
Innovation
Methods, ideas, or system contributions that make the work stand out.
tool orchestration
layered execution structure
reflective correction
schema-aware error handling
agentic systems
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2024-06-06Citations: 1
