Laura Climent

Orcid: 0000-0001-9453-5150

According to our database1, Laura Climent authored at least 25 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A framework for designing Reinforcement Learning agents with Dynamic Difficulty Adjustment in single-player action video games.
Entertain. Comput., 2024

2023
A hybrid metaheuristic with learning for a real supply chain scheduling problem.
Eng. Appl. Artif. Intell., November, 2023

Automatic assessment of object oriented programming assignments with unit testing in Python and a real case assignment.
Comput. Appl. Eng. Educ., September, 2023

2022
Iterated Local Search for the eBuses Charging Location Problem.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Large Neighborhood Search for Robust Solutions for Constraint Satisfaction Problems with Ordered Domains.
Proceedings of the 28th International Conference on Principles and Practice of Constraint Programming, 2022

2021
An analytics-based heuristic decomposition of a bilevel multiple-follower cutting stock problem.
OR Spectr., 2021

2020
Transition to eBuses with Minimal Timetable Disruptions.
Proceedings of the Thirteenth International Symposium on Combinatorial Search, 2020

Go with the Flow: Reinforcement Learning in Turn-based Battle Video Games.
Proceedings of the IVA '20: ACM International Conference on Intelligent Virtual Agents, 2020

2019
Analytics-Based Decomposition of a Class of Bilevel Problems.
Proceedings of the Optimization of Complex Systems: Theory, 2019

2017
Acquiring Local Preferences of Weighted Partial MaxSAT.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016
Extrapolating from Limited Uncertain Information in Large-Scale Combinatorial Optimization Problems to Obtain Robust Solutions.
Int. J. Artif. Intell. Tools, 2016

Uncertainty in dynamic constraint satisfaction problems.
AI Commun., 2016

An Improved Metaheuristic Algorithm for Maximizing Demand Satisfaction in the Population Harvest Cutting Stock Problem.
Proceedings of the Ninth Annual Symposium on Combinatorial Search, 2016

Bounding the Search Space of the Population Harvest Cutting Problem with Multiple Size Stock Selection.
Proceedings of the Learning and Intelligent Optimization - 10th International Conference, 2016

2015
Robustness and stability in dynamic constraint satisfaction problems.
Constraints An Int. J., 2015

Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings.
Artif. Intell. Rev., 2015

Solving a Hard Cutting Stock Problem by Machine Learning and Optimisation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Robustness and Stability in Constraint Programming under Dynamism and Uncertainty.
J. Artif. Intell. Res., 2014

Extrapolating from Limited Uncertain Information to Obtain Robust Solutions for Large-Scale Optimization Problems.
Proceedings of the 26th IEEE International Conference on Tools with Artificial Intelligence, 2014

Robustness and Stability in Constraint Programming under Dynamism and Uncertainty - (Extended Abstract).
Proceedings of the Principles and Practice of Constraint Programming, 2014

2013
Modeling Robustness in CSPs as Weighted CSPs.
Proceedings of the Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 2013

2012
An Algorithm for Finding Robust and Stable Solutions for Constraint Satisfaction Problems with Discrete and Ordered Domains.
Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

2011
Reformulating Dynamic Linear Constraint Satisfaction Problems as Weighted CSPs for Searching Robust Solutions.
Proceedings of the Ninth Symposium on Abstraction, Reformulation, and Approximation, 2011

2010
Robust Solutions in Changing Constraint Satisfaction Problems.
Proceedings of the Trends in Applied Intelligent Systems, 2010

2009
Stability of Solutions in Constraint Satisfaction Problems.
Proceedings of the Artificial Intelligence Research and Development, 2009


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