Leonardo Villalobos-Arias

According to our database, Leonardo Villalobos-Arias authored at least 14 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

General Flexible <i>f</i>-divergence for Challenging Offline RL Datasets with Low Stochasticity and Diverse Behavior Policies.

Jianxun Wang, Grant C. Forbes, Leonardo Villalobos-Arias, David L. Roberts

CoRR, February, 2026

2025

Minding Motivation: The Effect of Intrinsic Motivation on Agent Behaviors.

Leonardo Villalobos-Arias, Grant C. Forbes, Jianxun Wang, David L. Roberts, Arnav Jhala

CoRR, July, 2025

Action-Dependent Optimality-Preserving Reward Shaping.

Grant C. Forbes, Jianxun Wang, Leonardo Villalobos-Arias, Arnav Jhala, David I. Roberts

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Action-Dependent Optimality-Preserving Reward Shaping.

Grant C. Forbes, Jianxun Wang, Leonardo Villalobos-Arias, Arnav Jhala, David L. Roberts

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Potential-Based Intrinsic Motivation: Preserving Optimality With Complex, Non-Markovian Shaping Rewards.

Grant C. Forbes, Leonardo Villalobos-Arias, Jianxun Wang, Arnav Jhala, David L. Roberts

CoRR, 2024

Potential-Based Reward Shaping for Intrinsic Motivation.

Grant C. Forbes, Nitish Gupta, Leonardo Villalobos-Arias, Colin M. Potts, Arnav Jhala, David L. Roberts

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Modeling Risk in Reinforcement Learning: A Literature Mapping.

Leonardo Villalobos-Arias, Derek Martin, Abhijeet Krishnan, Madeleine Gagné, Colin M. Potts, Arnav Jhala

CoRR, 2023

2021

Hyper-Parameter Tuning of Classification and Regression Trees for Software Effort Estimation.

Leonardo Villalobos-Arias, Christian Quesada-López, Alexandra Martínez Porras, Marcelo Jenkins

Proceedings of the Trends and Applications in Information Systems and Technologies, 2021

Comparative study of random search hyper-parameter tuning for software effort estimation.

Leonardo Villalobos-Arias, Christian Quesada-López

Proceedings of the PROMISE '21: 17th International Conference on Predictive Models and Data Analytics in Software Engineering, 2021

Multi-objective hyper-parameter tuning for software effort estimation.

Leonardo Villalobos-Arias, Christian Quesada-López, Alexandra Martínez, Marcelo Jenkins

Proceedings of the 24th Iberoamerican Conference on Software Engineering, 2021

2020

Evaluation of a model-based testing platform for Java applications.

Leonardo Villalobos-Arias, Christian Quesada-López, Alexandra Martínez, Marcelo Jenkins

IET Softw., 2020

Evaluating hyper-parameter tuning using random search in support vector machines for software effort estimation.

Leonardo Villalobos-Arias, Christian Quesada-López, Jose Guevara-Coto, Alexandra Martínez, Marcelo Jenkins

Proceedings of the PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, 2020

2019

Model-based testing areas, tools and challenges: A tertiary study.

Leonardo Villalobos-Arias, Christian Quesada-López, Alexandra Martínez, Marcelo Jenkins

CLEI Electron. J., 2019

2018

A tertiary study on model-based testing areas, tools and challenges: Preliminary results.

Leonardo Villalobos-Arias, Christian Quesada-López, Alexandra Martínez, Marcelo Jenkins

Proceedings of the XXI Iberoamerican Conference on Software Engineering, 2018