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Proceedings ArticleDOI

Plan Repair Applied to Autonomous Underwater Vehicle Swarms

Helene Soubaras
- pp 989-994
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TLDR
This paper presents an application of a new plan repair algorithm proposed recently, the 15-puzzle algorithm with potential with potential to the concrete context of underwater autonomous vehicles mission planning.
Abstract
Plan repair is a field of AI planning which is related to plan execution since it requires the monitoring of the actions to be executed. This paper presents an application of a new plan repair algorithm we proposed recently, the 15-puzzle algorithm with potential [18]–[20] to the concrete context of underwater autonomous vehicles mission planning. In a multi-drone mission in underwater environment, one must repair a plan when a vehicle breaks down. We propose a model for the plan repair problem and show results obtained with our algorithm.

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References
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Proceedings Article

Fast plan adaptation through planning graphs: local and systematic search techniques

TL;DR: A domain-independent method for plan adaptation that combines two techniques that can be used either for solving a plan adaptation task or as a preprocessing for reducing the number of inconsistencies in the input plan.
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TL;DR: It is described how two representative state-of-the-art domain independent planning approaches - one based on compilation to CSP, and the other based on heuristic local search - can be adapted to produce diverse plans.
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Ant systems & Local Search Optimization for flexible Job Shop Scheduling Production

TL;DR: Two closely related approaches to the resolution of the flexible job shop scheduling production system are described, which combine the Ant system optimisation meta-heuristic (AS) with local search methods, including tabu search.
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A novel genetic algorithm for flexible job shop scheduling problems with machine disruptions

TL;DR: In this article, a genetic algorithm with very special chromosome encoding is proposed to handle flexible job shop scheduling that can adapt to disruption to reflect more closely the real-world manufacturing environment.
Book ChapterDOI

Variable Neighborhood Genetic Algorithm for the Flexible Job Shop Scheduling Problems

TL;DR: A Variable Neighborhood Genetic Algorithm (VNGA) is proposed for the problem with makespan criterion, consisting of a combination of the variable neighborhood search (VNS) and genetic algorithm (GA).