12 citations · 19 across the 8 of their papers we have counts for
8 papers
Performance-guided Task-specific Optimization for Multirotor Design
Etor Arza, Welf Rehberg, Philipp Weiss +2
This paper introduces a methodology for task-specific design optimization of multirotor Micro Aerial Vehicles. By leveraging reinforcement learning, Bayesian optimization, and cova…
A Review on Single-Problem Multi-Attempt Heuristic Optimization
Judith Echevarrieta, Etor Arza, Aritz Pérez +1
In certain real-world optimization scenarios, practitioners are not interested in solving multiple problems but rather in finding the best solution to a single, specific problem. W…
An Empirical Study on the Computation Budget of Co-Optimization of Robot Design and Control in Simulation
Etor Arza, Frank Veenstra, Tønnes F. Nygaard +1
The design (shape) of a robot is usually decided before the control is implemented. This might limit how well the design is adapted to a task, as the suitability of the design is g…
Speeding-up Evolutionary Algorithms to solve Black-Box Optimization Problems
Judith Echevarrieta, Etor Arza, Aritz Pérez
Population-based evolutionary algorithms are often considered when approaching computationally expensive black-box optimization problems. They employ a selection mechanism to choos…
Generalized Early Stopping in Evolutionary Direct Policy Search
Etor Arza, Leni K. Le Goff, Emma Hart
Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g…
On the Fair Comparison of Optimization Algorithms in Different Machines
Etor Arza, Josu Ceberio, Ekhiñe Irurozki +1
An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the s…
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach
Etor Arza, Josu Ceberio, Ekhiñe Irurozki +1
Non-deterministic measurements are common in real-world scenarios: the performance of a stochastic optimization algorithm or the total reward of a reinforcement learning agent in a…
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
Etor Arza, Aritz Perez, Ekhine Irurozki +1
The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivat…