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Found 3 papers, 2 papers with code
Water-Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP-Hard Problems
Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization.
Density-based Feasibility Learning with Normalizing Flows for Introspective Robotic Assembly
Machine Learning (ML) models in Robotic Assembly Sequence Planning (RASP) need to be introspective on the predicted solutions, i. e. whether they are feasible or not, to circumvent potential efficiency degradation.
Efficient and Feasible Robotic Assembly Sequence Planning via Graph Representation Learning
With GRACE, we are able to extract meaningful information from the graph input and predict assembly sequences in a step-by-step manner.
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