Search Results for author: Andrés Weintraub

Found 2 papers, 0 papers with code

Advancing Forest Fire Prevention: Deep Reinforcement Learning for Effective Firebreak Placement

no code implementations12 Apr 2024 Lucas Murray, Tatiana Castillo, Jaime Carrasco, Andrés Weintraub, Richard Weber, Isaac Martín de Diego, José Ramón González, Jordi García-Gonzalo

To the best of our knowledge, this study represents a pioneering effort in using Reinforcement Learning to address the aforementioned problem, offering promising perspectives in fire prevention and landscape management

Q-Learning reinforcement-learning +1

Comparison of metaheuristics for the firebreak placement problem: a simulation-based optimization approach

no code implementations29 Nov 2023 David Palacios-Meneses, Jaime Carrasco, Sebastián Dávila, Maximiliano Martínez, Rodrigo Mahaluf, Andrés Weintraub

The problem of firebreak placement is crucial for fire prevention, and its effectiveness at landscape scale will depend on their ability to impede the progress of future wildfires.

Stochastic Optimization

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