Michael Caldara — accepted AI-conference papers

2026

Symbolic Planning and Multi-Agent Path Finding in Extremely Dense Environments with Unassigned Agents

Bo Fu, Zhe Chen, Rahul Chandan, Alexandre Ormiga Galvao Barbosa, Michael Caldara, Joey W. Durham +1

AAAI 2026technical

We introduce the Block Rearrangement Problem (BRaP), a challenging component of large warehouse management which involves rearranging storage blocks within dense grids to achieve a goal state. We formally define the BRaP as a graph search problem. Building on intuitions from sliding puzzle problems,

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2025

Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping

Guangyi Liu, Suzan Iloglu, Michael Caldara, Joseph W Durham, Michael M. Zavlanos

ICML 2025poster

In Amazon robotic warehouses, the destination-to-chute mapping problem is crucial for efficient package sorting. Often, however, this problem is complicated by uncertain and dynamic package induction rates, which can lead to increased package recirculation. To tackle this challenge, we introduce a D…

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