Rodrigo Toro Icarte

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 28

Top Topics

Accomplish Tasks

Formal Languages

Reward Function

Reinforcement Learning

Top Venues

Canadian Conference on AI

Publications

Andrew C. Li, Zizhao Chen, Toryn Q. Klassen, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith
Reward Machines for Deep RL in Noisy and Uncertain Environments. CoRR (2024)
Phillip J. K. Christoffersen, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior. CoRR (2023)
Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Learning Belief Representations for Partially Observable Deep RL. ICML (2023)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Ethan Waldie, Sheila A. McIlraith
Learning reward machines: A study in partially observable reinforcement learning. Artif. Intell. 323 (2023)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. J. Artif. Intell. Res. 73 (2022)
Andrew C. Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith
Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks. CoRR (2022)
Jaime Middleton, Rodrigo Toro Icarte, Jorge A. Baier
Real-Time Heuristic Search with LTLf Goals. IJCAI (2022)
Andrew C. Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines. CoRR (2022)
Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. AAMAS (2022)
Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. Canadian Conference on AI (2021)
Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning. CoRR (2021)
Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. ICML (2021)
Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Be Considerate: Objectives, Side Effects, and Deciding How to Act. CoRR (2021)
Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Interpretable Sequence Classification via Discrete Optimization. AAAI (2021)
Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. CoRR (2021)
Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. CoRR (2021)
Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Interpretable Sequence Classification via Discrete Optimization. CoRR (2020)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. CoRR (2020)
León Illanes, Xi Yan, Rodrigo Toro Icarte, Sheila A. McIlraith
Symbolic Plans as High-Level Instructions for Reinforcement Learning. ICAPS (2020)
Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith
The act of remembering: a study in partially observable reinforcement learning. CoRR (2020)
Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith
Learning Reward Machines for Partially Observable Reinforcement Learning. NeurIPS (2019)
Rodrigo Toro Icarte, León Illanes, Margarita P. Castro, André A. Ciré, Sheila A. McIlraith, J. Christopher Beck
Training Binarized Neural Networks Using MIP and CP. CP (2019)
Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. IJCAI (2019)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Advice-Based Exploration in Model-Based Reinforcement Learning. Canadian Conference on AI (2018)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning. ICML (2018)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Teaching Multiple Tasks to an RL Agent using LTL. AAMAS (2018)
Rodrigo Toro Icarte, Jorge A. Baier, Cristian Ruz, Alvaro Soto
How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval. CoRR (2017)
Rodrigo Toro Icarte, Jorge A. Baier, Cristian Ruz, Alvaro Soto
How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval. IJCAI (2017)