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ORCIDRodrigo Toro Icarte
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2020 – today
- 2024
[c15]Alvaro Labarca, Denis Parra, Rodrigo Toro Icarte:
On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation. ICML 2024- [i13]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 abs/2406.00120 (2024) - [i12]Parand A. Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI. CoRR abs/2411.10613 (2024) - 2023
- [j2]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: 103989 (2023) - [c14]Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Learning Belief Representations for Partially Observable Deep RL. ICML 2023: 35970-35988 - [i11]Phillip J. K. Christoffersen, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior. CoRR abs/2301.02952 (2023) - 2022
- [b1]Rodrigo Toro Icarte:
Reward Machines. University of Toronto, Canada, 2022 - [j1]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: 173-208 (2022) - [c13]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. AAMAS 2022: 18-26 - [c12]Jaime Middleton, Rodrigo Toro Icarte, Jorge A. Baier:
Real-Time Heuristic Search with LTLf Goals. IJCAI 2022: 4785-4792 - [i10]Andrew C. Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith:
Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks. CoRR abs/2206.01812 (2022) - [i9]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 abs/2211.10902 (2022) - 2021
- [c11]Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Interpretable Sequence Classification via Discrete Optimization. AAAI 2021: 9647-9656 - [c10]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 AI 2021 - [c9]Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. ICML 2021: 10497-10508 - [i8]Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. CoRR abs/2102.06858 (2021) - [i7]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 abs/2106.00133 (2021) - [i6]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Objectives, Side Effects, and Deciding How to Act. CoRR abs/2106.02617 (2021) - [i5]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 abs/2112.09477 (2021) - 2020
- [c8]León Illanes, Xi Yan, Rodrigo Toro Icarte, Sheila A. McIlraith:
Symbolic Plans as High-Level Instructions for Reinforcement Learning. ICAPS 2020: 540-550 - [i4]Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip J. K. Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith:
The act of remembering: a study in partially observable reinforcement learning. CoRR abs/2010.01753 (2020) - [i3]Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith:
Interpretable Sequence Classification via Discrete Optimization. CoRR abs/2010.02819 (2020) - [i2]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. CoRR abs/2010.03950 (2020)
2010 – 2019
- 2019
- [c7]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: 401-417 - [c6]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: 6065-6073 - [c5]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: 15497-15508 - 2018
- [c4]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Advice-Based Exploration in Model-Based Reinforcement Learning. Canadian AI 2018: 72-83 - [c3]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Teaching Multiple Tasks to an RL Agent using LTL. AAMAS 2018: 452-461 - [c2]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: 2112-2121 - 2017
- [c1]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: 1283-1289 - [i1]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 abs/1705.08844 (2017)
Coauthor Index
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