Backward time-reversed conflict-based search finds initial collision-free simultaneous-arrival trajectories for agents at rest, which are then refined via distributed nonlinear ADMM optimal control.
A survey of distributed optimization,
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3verdicts
UNVERDICTED 3representative citing papers
Decentralized gradient descent tracks the minimizer of temporally weighted streaming objectives, achieving O(1/t) fixed-point tracking under uniform weights and a non-vanishing floor under exponential discounting, plus a heterogeneity-induced bias floor.
A fully distributed primal-dual algorithm solves nonsmooth strongly convex problems with coupled constraints on time-varying digraphs at O(1/k) rate without communicating primal variables.
citing papers explorer
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Multi-Agent Motion Planning for Simultaneous Arrival using Time-Reversed Search and Distributed Optimal Control
Backward time-reversed conflict-based search finds initial collision-free simultaneous-arrival trajectories for agents at rest, which are then refined via distributed nonlinear ADMM optimal control.
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Decentralized Time-Varying Optimization for Streaming Data via Temporal Weighting
Decentralized gradient descent tracks the minimizer of temporally weighted streaming objectives, achieving O(1/t) fixed-point tracking under uniform weights and a non-vanishing floor under exponential discounting, plus a heterogeneity-induced bias floor.
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Distributed Optimization with Coupled Constraints over Time-Varying Digraph
A fully distributed primal-dual algorithm solves nonsmooth strongly convex problems with coupled constraints on time-varying digraphs at O(1/k) rate without communicating primal variables.