Rodrigo Toro Icarte

According to our database, Rodrigo Toro Icarte authored at least 22 papers between 2017 and 2023.

Collaborative distances:

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

2023

Learning reward machines: A study in partially observable reinforcement learning.

Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Ethan Waldie, Sheila A. McIlraith

Artif. Intell., October, 2023

Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior.

Phillip J. K. Christoffersen, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith

CoRR, 2023

Learning Belief Representations for Partially Observable Deep RL.

Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

Proceedings of the International Conference on Machine Learning, 2023

2022

Reward Machines.

Rodrigo Toro Icarte

PhD thesis, 2022

Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning.

Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith

J. Artif. Intell. Res., 2022

Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines.

Andrew C. Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

CoRR, 2022

Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks.

Andrew C. Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith

CoRR, 2022

Real-Time Heuristic Search with LTLf Goals.

Jaime Middleton, Rodrigo Toro Icarte, Jorge A. Baier

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning.

Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

Be Considerate: Objectives, Side Effects, and Deciding How to Act.

Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

CoRR, 2021

LTL2Action: Generalizing LTL Instructions for Multi-Task RL.

Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith

Proceedings of the 38th International Conference on Machine Learning, 2021

AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning.

Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith

Proceedings of the 34th Canadian Conference on Artificial Intelligence, 2021

Interpretable Sequence Classification via Discrete Optimization.

Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

The act of remembering: a study in partially observable reinforcement learning.

Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip J. K. Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith

CoRR, 2020

Symbolic Plans as High-Level Instructions for Reinforcement Learning.

León Illanes, Xi Yan, Rodrigo Toro Icarte, Sheila A. McIlraith

Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, 2020

2019

Learning Reward Machines for Partially Observable Reinforcement Learning.

Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning.

Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Training Binarized Neural Networks Using MIP and CP.

Rodrigo Toro Icarte, León Illanes, Margarita P. Castro, André A. Ciré, Sheila A. McIlraith, J. Christopher Beck

Proceedings of the Principles and Practice of Constraint Programming, 2019

2018

Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning.

Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith

Proceedings of the 35th International Conference on Machine Learning, 2018

Teaching Multiple Tasks to an RL Agent using LTL.

Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Advice-Based Exploration in Model-Based Reinforcement Learning.

Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith

Proceedings of the Advances in Artificial Intelligence, 2018

2017

How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval.

Rodrigo Toro Icarte, Jorge A. Baier, Cristian Ruz, Alvaro Soto

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017