An elimination-based rejection-sampling algorithm with optimistic evaluators identifies target-feasible antichains in monotone co-design problems and propagates bounds compositionally through multigraphs.
Applied Compositional Thinking for Engineering
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A compositional framework based on monotone co-design theory enables joint optimization of robot design, fleet composition, and planning for heterogeneous multi-robot systems under task-specific constraints.
citing papers explorer
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Compositional Online Learning for Multi-Objective System Co-Design
An elimination-based rejection-sampling algorithm with optimistic evaluators identifies target-feasible antichains in monotone co-design problems and propagates bounds compositionally through multigraphs.
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Task-Driven Co-Design of Heterogeneous Multi-Robot Systems
A compositional framework based on monotone co-design theory enables joint optimization of robot design, fleet composition, and planning for heterogeneous multi-robot systems under task-specific constraints.