Alain Andres Fernandez

Alain Andres Fernandez

Data Scientist at TECNALIA, Lecturer in Deusto University

Supervision

Language as a Beacon: Guiding Reinforcement Learning with High-Level Language Prompts for Better Exploration and Generalization

Supervisors: Alain Andres , Javier Del Ser

Student: Unai Ruiz González (M.S.) , 2023-2024

Abstract: In the last decade, artificial intelligence has undergone a remarkable revolution, highlighted by the advances of Large Language Models (LLMs). Concurrently, the field of Reinforcement Learning (RL) has grown exponentially, expanding from robotics to personalized recommendation systems. In this context, the convergence of both fields seems promising. This convergence has the potential to further enhance agents’ ability to learn efficiently, redefining the possibilities of artificial intelligence application and, consequently, its impact on everyday life. Read more

A Reinforcement Learning-Based Approach for Vehicle Platoon Route Optimization in Last-Mile Delivery

Supervisors: Alain Andres , Imanol Echeverria , Roberto Santana

Student: Nagore Bravo Julián (B.S.) , 2023-2024

Abstract: Classic challenges in combinatorial optimization, such as the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), have practical applications in planning, logistics, and transportation. Traditionally, these problems have been extensively studied using exact, heuristic, and meta-heuristic methods. However, the issue of generating high-quality solutions in real time persists, as these methods require starting from scratch each time a new problem needs to be solved. This is where the use of Reinforcement Learning (RL) emerges as a promising alternative for solving combinatorial optimization problems in real time. Time is a crucial factor in real-world routing problems, where conditions can change rapidly and solutions must adapt efficiently to these variations. Read more

Anomaly Detection in Wind Turbines: Analysis of Data Imbalance and Temporal Effects

Supervisors: Amaia Abanda , Alain Andres , Uxue Mori

Student: Ane San Jose (B.S.) , 2023-2024

Abstract: In engineering and systems monitoring, an anomaly is defined as a rare event. Detecting these anomalies, which deviate significantly from expected or normal system behavior, is crucial for identifying issues in various contexts, including computer systems and industrial processes. Read more

Trajectory Planning for a Robotic Arm Using Reinforcement Learning

Supervisors: Alain Andres , Jon Azpiazu , Eduardo Zamudio

Student: Sergio Garcia Ferreira (M.S.) , 2022-2023

Abstract: Reinforcement Learning has brought about a transformation in robotics, thanks to its ability to develop efficient control techniques through autonomous learning. In particular, Reinforcement Learning has proven to be successful in tasks such as reaching objects with robotic arms. In this work, a solution is developed for training this task in simulated environments, and an experimental setup is established to compare the performance of various model-free algorithms. It is demonstrated that PPO achieves the best results, while SAC exhibits instability in environments with Dense rewards. Furthermore, it is concluded that a Sparse reward is sufficient to solve the task in environments with a precision of 5 cm. Read more