Publications

Journal Articles

1. Iván Astete, Margarita Castro, Álvaro Lorca, Matías Negrete-Pincetic, Optimal cleaning scheduling for large photovoltaic portfolio. Applied Energy,2024.

2. Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Sheila A. McIlraith, Learning Reward Machines: A Study in Partially Observable Reinforcement Learning. Artificial Intelligence, 2023 [post-print]

3. Lucas Maulén, Margarita Castro, Álvaro Lorca, Matías Negrete-Pincetic, Optimization-based expansion planning for power and hydrogen systems with feedback from a unit commitment model. Applied Energy,2023.

4. Ryo Kuroiwa, Alexander Shleyfman, Chiara Piacentini, Margarita P. Castro, J. Christopher Beck, The LM-Cut Heuristic Family for Optimal Numeric Planning with Simple Conditions. Journal of Artificial Intelligence Research, 2022.

5. Margarita P. Castro, Andre A. Cire, J. Christopher Beck, Decision Diagrams for Discrete Optimization: A Survey of Recent Advances. INFORMS Journal on Computing, 2022, 34(4), 1841-2382. [arXiv]

6. Margarita P. Castro, Andre A. Cire, J. Christopher Beck, A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Second-Order Conic Programming.  Mathematical Programming, 2021, (in press). (Winner CORS Student Paper Competition) (Runner-up ICS Student Paper Award) [arXiv][DOT-video][code]

7. Margarita P. Castro, Andre A. Cire, J. Christopher Beck, An MDD-based Lagrangian Approach to the Multi-Commodity Pickup-and-Delivery TSP. INFORMS Journal on Computing, 2020, 32(2), 263-278. [post-print][appendix] [code]

8. Margarita P. Castro, Chiara Piacentini, Andre A. Cire, J. Christopher Beck, Relaxed Decision Diagram Based Heuristics for Delete-Free Planning Tasks. Journal of Artificial Intelligence Research, 2020, 67:607-651. [post-print][code (coming soon)]

9. Michael Morin, Margarita P. Castro, Kyle E.C. Booth, Tony T. Tran, Chang Liu, J. Christopher Beck, Intruder Alert! Optimization Models for Solving the Mobile Robot Graph-Clear Problem. Constraints, 2018, 23: 335-354. (CPAIOR Distinguished Paper Award). [post-print] 

Under Review:

1. Nicolás Casassus, Margarita P. Castro, Gustavo Angulo, A Decision Diagram Approach for the Parallel Machine Scheduling Problem with Chance Constraints [arXiv] [OO]

2. Margarita P. Castro, Merve Bodur, Amer Shalaby Song, Incorporating Service Reliability in Multi-depot Vehicle Scheduling. 2025 [post-print 1]

3. Margarita P. Castro, Merve Bodur, Yongjia Song, Markov Chain-based Policies for Multi-stage Stochastic Integer Linear Programming with an Application to Disaster Relief Logistics. 2022 [post-print 1][post-print 2]

4.  Enzo Sauma,  Andres Pereira, Francisco Manriquez, Sonia Vera, Francisca Jalil-Vega, Margarita P. Castro, The Role of Kirchhoff's Voltage Law in Assessing the Impact of Climate Change on Power Systems. (Under Review)

Peer-reviewed Conference Papers

1. Ryo Kuroiwa, Alexander Shleyfman, Chiara Piacentini, Margarita P. Castro, J. Christopher Beck, LM-Cut and Operator Counting Heuristics for Optimal Numeric Planning with Simple Conditions. International Conference on Automated Planning and Scheduling (ICAPS-21), 2021. 210-218.

2. Margarita P. Castro, Meinolf Sellmann, Zhaoyuan Yang, Nurali Virani, Empirical Confidence Models for Supervised Machine Learning. Canadian Conference on Artificial Intelligence (Canadian AI-20), 2020, 105-117.

3. Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Sheila A. McIlraith,  Learning Reward Machines for Partially Observable Reinforcement Learning. Conference on Neural Information Processing Systems (NeurIPS-19), 2019, 15497-15508 (Spotlight talk - top 10% of accepted papers). [post-print]

4. Rodrigo Toro Icarte,  León Illanes,  Margarita P. Castro, Andre A. Cire, Sheila A. McIlraith,  J. Christopher Beck, Training Binarized Neural Networks using MIP and CP.  International Conference on Principles and Practice of Constraint Programming (CP-19), 2019. 401-417. [post-print] [code]

5. Margarita P. Castro, Chiara Piacentini,  Andre A. Cire.,  J. Christopher Beck, Relaxed BDDs: An Admissible Heuristic for Delete-Free Planning Based on a Discrete Relaxation. International Conference on Automated Planning and Scheduling (ICAPS-19), 2019. 77-85. [post-print]

6. Chiara Piacentini,  Margarita P. Castro, Andre A. Cire., J. Christopher Beck, Compiling Optimal Numeric Planning to Mixed Integer Linear Programming. International Conference on Automated Planning and Scheduling (ICAPS-18), 2018. 383-387. [post-print] [appendix]

7. Chiara Piacentini,  Margarita P. Castro, Andre A. Cire., J. Christopher Beck, Linear and Integer Programming-based Heuristics for Cost-optimal Numeric Planning. AAAI Conference on Artificial Intelligence (AAAI-18), 2018. 6254-6261. [post-print]

Peer-reviewed Workshop Papers

1. Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro,  Sheila A. McIlraith, Searching for Markovian Subproblems to Address Partially Observable Reinforcement Learning. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2019. [post-print]

2.  Margarita P. Castro, Chiara Piacentini, Andre A. Cire, J. Christopher Beck, Relaxed Decision Diagrams for Cost-Optimal Classical Planning. Workshop on Heuristics and Search for Domain-independent Planning (HSDIP-18), 2018. 50-58. [post-print]

Ph.D. Dissertation

Margarita P. Castro, Optimization Methods Based on Decision Diagrams for Constraint Programming, AI Planning, and Mathematical Programming, 2021. (ACP Doctoral Research Award). [post-print] [CP talk]