Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization

• URL: http://arxiv.org/abs/2606.00008v1
• Date: Fri, 27 Mar 2026 14:21:21 GMT
• Title: Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimization
• Abstract summary: Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives.<n>We propose ATOM, a multi-agent framework that formulates molecular optimization as a tree-structured search.
• Score: 33.33321738135092
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly constrain downstream outcomes. Existing methods typically rely on a single policy or fixed scalarization, which limits their ability to represent diverse trade-offs and to explore multiple promising design trajectories. We propose ATOM, a multi-agent framework that formulates molecular optimization as a tree-structured search. Each node corresponds to an atomic operation and hosts an agent specialized for a particular objective or decision context. Agents coordinate along different paths of the tree rather than enforcing a global consensus, enabling the method to maintain and compare alternative molecular evolution trajectories. A global memory of past optimization behaviors further supports balanced exploration and exploitation across objectives. This tree-structured interaction enables reasoning over long-horizon dependencies inherent in molecular design. Experiments on challenging multi-objective benchmarks involving activity, synthesizability, and ADMET-related properties show that ATOM consistently achieves improved Pareto coverage and hypervolume over strong baselines. These results demonstrate the effectiveness of pathwise multi-agent coordination for molecular optimization. Code is available at https://anonymous.4open.science/r/ATOM-41CE.

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