36 citations · 236 across the 52 of their papers we have counts for
23 papers · 1 filter
MultiZenoTravel: a Tunable Benchmark for Multi-Objective Planning with Known Pareto Front
Alexandre Quemy, Marc Schoenauer, Johann Dreo
Multi-objective AI planning suffers from a lack of benchmarks exhibiting known Pareto Fronts. In this work, we propose a tunable benchmark generator, together with a dedicated solv…
DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification
Julien Girard-Satabin, Aymeric Varasse, Marc Schoenauer +2
The impressive results of modern neural networks partly come from their non linear behaviour. Unfortunately, this property makes it very difficult to apply formal verification tool…
Anomaly Detection with the Voronoi Diagram Evolutionary Algorithm
Marti Luis, Fansi-Tchango Arsene, Navarro Laurent +1
This paper presents the Voronoi diagram-based evolutionary algorithm (VorEAl). VorEAl partitions input space in abnormal/normal subsets using Voronoi diagrams. Diagrams are evolved…
Racing Multi-Objective Selection Probabilities
Gaétan Marceau, Marc Schoenauer
In the context of Noisy Multi-Objective Optimization, dealing with uncertainties requires the decision maker to define some preferences about how to handle them, through some stati…
Multiobjective Tactical Planning under Uncertainty for Air Traffic Flow and Capacity Management
Gaétan Marceau, Pierre Savéant, Marc Schoenauer
We investigate a method to deal with congestion of sectors and delays in the tactical phase of air traffic flow and capacity management. It relies on temporal objectives given for…
Computational Methods for Probabilistic Inference of Sector Congestion in Air Traffic Management
Gaétan Marceau, Pierre Savéant, Marc Schoenauer
This article addresses the issue of computing the expected cost functions from a probabilistic model of the air traffic flow and capacity management. The Clenshaw-Curtis quadrature…
Strategic Planning in Air Traffic Control as a Multi-objective Stochastic Optimization Problem
Gaétan Marceau, Pierre Savéant, Marc Schoenauer
With the objective of handling the airspace sector congestion subject to continuously growing air traffic, we suggest to create a collaborative working plan during the strategic ph…
Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning
Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal +2
Parameter tuning is recognized today as a crucial ingredient when tackling an optimization problem. Several meta-optimization methods have been proposed to find the best parameter…
Multi-Objective AI Planning: Comparing Aggregation and Pareto Approaches
Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal +2
Most real-world Planning problems are multi-objective, trying to minimize both the makespan of the solution plan, and some cost of the actions involved in the plan. But most, if no…
Multi-Objective AI Planning: Evaluating DAE-YAHSP on a Tunable Benchmark
Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal +2
All standard AI planners to-date can only handle a single objective, and the only way for them to take into account multiple objectives is by aggregation of the objectives. Further…
Increasing Air Traffic: What is the Problem?
Areski Hadjaz, Gaétan Marceau, Pierre Savéant +1
Nowadays, huge efforts are made to modernize the air traffic management systems to cope with uncertainty, complexity and sub-optimality. An answer is to enhance the information sha…
Evolving Genes to Balance a Pole
Miguel Nicolau, Marc Schoenauer, W. Banzhaf
We discuss how to use a Genetic Regulatory Network as an evolutionary representation to solve a typical GP reinforcement problem, the pole balancing. The network is a modified vers…
Robust Multi-Cellular Developmental Design
Alexandre Devert, Nicolas Bredèche, Marc Schoenauer
This paper introduces a continuous model for Multi-cellular Developmental Design. The cells are fixed on a 2D grid and exchange "chemicals" with their neighbors during the growth p…
Evolving Symbolic Controllers
Nicolas Godzik, Marc Schoenauer, Michèle Sebag
The idea of symbolic controllers tries to bridge the gap between the top-down manual design of the controller architecture, as advocated in Brooks' subsumption architecture, and th…
Ensemble Learning for Free with Evolutionary Algorithms ?
Christian Gagné, Michèle Sebag, Marc Schoenauer +1
Evolutionary Learning proceeds by evolving a population of classifiers, from which it generally returns (with some notable exceptions) the single best-of-run classifier as final re…
On the Benefits of Inoculation, an Example in Train Scheduling
Yann Semet, Marc Schoenauer
The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly c…
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Christian Gagné, Marc Schoenauer, Michèle Sebag +1
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed optimization p…
Using Domain Knowledge in Evolutionary System Identification
Marc Schoenauer, Michèle Sebag
Two example of Evolutionary System Identification are presented to highlight the importance of incorporating Domain Knowledge: the discovery of an analytical indentation law in Str…
Divide-and-Evolve: a New Memetic Scheme for Domain-Independent Temporal Planning
Marc Schoenauer, Pierre Savéant, Vincent Vidal
An original approach, termed Divide-and-Evolve is proposed to hybridize Evolutionary Algorithms (EAs) with Operational Research (OR) methods in the domain of Temporal Planning Prob…
Evolution of Voronoi based Fuzzy Recurrent Controllers
Carlos Kavka, Patricia Roggero, Marc Schoenauer
A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. Among the most successful methods to autom…
Evolutionary Computing
Aguston E. Eiben, Marc Schoenauer
Evolutionary computing (EC) is an exciting development in Computer Science. It amounts to building, applying and studying algorithms based on the Darwinian principles of natural se…
ATNoSFERES revisited
Samuel Landau, Olivier Sigaud, Marc Schoenauer
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens of…
Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms
Olga Roudenko, Marc Schoenauer
In spite of the recent quick growth of the Evolutionary Multi-objective Optimization (EMO) research field, there has been few trials to adapt the general variation operators to the…