ChaosNetBench is a tunable synthetic benchmark for STGNNs on chaotic lattice dynamics that shows graph models outperform non-graph baselines at high local and global chaos.
International Conference on Learning Representations (ICLR) , year=
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OLSF-TRS is a generalized sequential decision framework using structured combinatorial optimization and multi-agent reinforcement learning for order-tote-robot coordination in tote-handling robotic systems, with near-optimal performance on small scales and 8-30%+ improvements over heuristics onlarge
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ChaosNetBench: Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamics
ChaosNetBench is a tunable synthetic benchmark for STGNNs on chaotic lattice dynamics that shows graph models outperform non-graph baselines at high local and global chaos.
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Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems
OLSF-TRS is a generalized sequential decision framework using structured combinatorial optimization and multi-agent reinforcement learning for order-tote-robot coordination in tote-handling robotic systems, with near-optimal performance on small scales and 8-30%+ improvements over heuristics onlarge