del Rio, F., Raymond-Sáez, A., Florea, D., Icarte, R. T., Hurtado, J., Calderon, C. B., & Soto, A. (2025). Data Distributional Properties As Inductive Bias for Systematic Generalization. In Proceedings of the Computer Vision and Pattern Recognition Conference (pp. 25590-25601). (2025)

Data Distributional Properties As Inductive Bias for Systematic Generalization

Proceedings of the Computer Vision and Pattern Recognition Conference

Sanabria P., Montoya S., Neyem A., Toro R., Hirsch M., Mateos C. (2024)

Connection-Aware Heuristics for Scheduling and Distributing Jobs under Dynamic Dew Computing Environments

Applied Sciences-Basel 14 8

Álvaro Labarca Silva, Denis Parra, Rodrigo Toro Icarte Proceedings of the 41st International Conference on Machine Learning, PMLR 235:45432-45450, 2024. (2024)

On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation

Proceedings of the 41st International Conference on Machine Learning, PMLR 235:45432-45450

Labarca A., Parra D., Toro R. (2024)

On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation

Proceedings of the 41st International Conference on Machine Learning

Li, A. C., Chen, Z., Klassen, T. Q., Vaezipoor, P., Toro Icarte, R., & McIlraith, S. A. (2024)

Reward Machines for Deep RL in Noisy and Uncertain Environments

38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Li, A. C., Chen, Z., Klassen, T. Q., Vaezipoor, P., Toro Icarte, R., & McIlraith, S. A. (2024). Reward Machines for Deep RL in Noisy and Uncertain Environments. In Proceedings of the 37th Conference on Advances in Neural Information Processing Systems, 2024. (2024)

Reward Machines for Deep RL in Noisy and Uncertain Environments

Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

Wang A., Li A.C., Klassen T.Q., Toro Icarte R. Mcilraith S.A. (2023)

Learning Belief Representations for Partially Observable Deep RL

Proceedings of the 40th International Conference on Machine Learning 202 35970-35988

Klassen T., Valenzano R., Castro M., Waldie E., Mcilraith S., Toro R. (2023)

Learning reward machines: A study in partially observable reinforcement learning 

ARTIFICIAL INTELLIGENCE 323

Alizadeh-Alamdari P., Klassen T. Q., Toro-Icarte R., McIlraith S. A. (2022)

Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems  18-26

Middleton, J., Toro Icarte, R., & Baier, J. (2022). Real-Time Heuristic Search with LTLf Goals. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (pp. 4785-4792). (2022)

Real-Time Heuristic Search with LTLf Goals

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence 4785-4792

Toro R., Klassen T. Q., Valenzano R., McIlraith S.A. (2022)

Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning

Journal of Artificial Intelligence Research 73 73-208

Sanabria P., Tapia T.F., Toro Icarte R., Neyem A. (2022)

Solving Task Scheduling Problems in Dew Computing via Deep Reinforcement Learning

Applied Sciences 12 14 7137