Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery

Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery

|Authors: Aditya Dutta, Joon-Seok Kim

|Venue: arXiv preprint | Year: 2026

|arXiv: 2607.15182v1

Abstract

Automated fulfillment warehouses must continuously assign and execute pickup-and-delivery work while avoiding congestion. In many-to-many Multi-Agent Pickup and Delivery (MAPD), a request specifies a stock-keeping unit rather than fixed endpoints, requiring the controller to select an agent, source, and destination before path planning. Existing graph-guidance methods primarily influence routing after goals are fixed, leaving endpoint instantiation uninformed by recent traffic. We introduce Stigmergic Graph Memory (SGM), a bounded, decaying memory layer that records recent execution signals on warehouse nodes and directed edges to rank feasible endpoints and route preferences without altering collision constraints or planner validity. Across paired request streams on five layouts, three load levels, and 25 seeds per condition, SGM outperforms two reconstructed many-to-many allocation baselines in all 15 map-load conditions, with paired throughput gains of 20.5-36.7%. These results show that recent execution memory can improve warehouse throughput by shaping which feasible goals enter the planner, not only how agents travel to already fixed goals.

Key Contributions

• Automated fulfillment warehouses must continuously assign and execute pickup-and-delivery work wh…
• In many-to-many Multi-Agent Pickup and Delivery (MAPD), a request specifies a stock-keeping unit …
• Existing graph-guidance methods primarily influence routing after goals are fixed, leaving endpoi…
• We introduce Stigmergic Graph Memory (SGM), a bounded, decaying memory layer that records recent …
• Across paired request streams on five layouts, three load levels, and 25 seeds per condition, SGM…

Topics

• vla
• planning
• control

Code & Data

No code repository linked in paper metadata.

BibTeX

@article{Dutta2026_260715182v1,
  title     = {Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery},
  author    = {Aditya Dutta and Joon-Seok Kim},
  year      = {2026},
  eprint    = {2607.15182v1},
  archivePrefix = {arXiv},
  primaryClass  = {cs.MA},
  url       = {https://arxiv.org/abs/2607.15182v1}
}