Margarita P. Castro

According to our database, Margarita P. Castro authored at least 15 papers between 2018 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

Optimization methods based on decision diagrams for constraint programming, AI planning, and mathematical programming.

Margarita P. Castro

Constraints An Int. J., September, 2023

2022

A combinatorial cut-and-lift procedure with an application to 0-1 second-order conic programming.

Margarita P. Castro, André Augusto Ciré, J. Christopher Beck

Math. Program., 2022

The LM-Cut Heuristic Family for Optimal Numeric Planning with Simple Conditions.

Ryo Kuroiwa, Alexander Shleyfman, Chiara Piacentini, Margarita P. Castro, J. Christopher Beck

J. Artif. Intell. Res., 2022

Decision Diagrams for Discrete Optimization: A Survey of Recent Advances.

Margarita P. Castro, André Augusto Ciré, J. Christopher Beck

INFORMS J. Comput., 2022

2021

LM-cut and Operator Counting Heuristics for Optimal Numeric Planning with Simple Conditions.

Ryo Kuroiwa, Alexander Shleyfman, Chiara Piacentini, Margarita P. Castro, J. Christopher Beck

Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

2020

Solving Delete Free Planning with Relaxed Decision Diagram Based Heuristics.

Margarita P. Castro, Chiara Piacentini, André Augusto Ciré, J. Christopher Beck

J. Artif. Intell. Res., 2020

An MDD-Based Lagrangian Approach to the Multicommodity Pickup-and-Delivery TSP.

Margarita P. Castro, André Augusto Ciré, J. Christopher Beck

INFORMS J. Comput., 2020

Empirical Confidence Models for Supervised Machine Learning.

Margarita P. Castro, Meinolf Sellmann, Zhaoyuan Yang, Nurali Virani

Proceedings of the Advances in Artificial Intelligence, 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

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

Relaxed BDDs: An Admissible Heuristic for Delete-Free Planning Based on a Discrete Relaxation.

Margarita P. Castro, Chiara Piacentini, André A. Ciré, J. Christopher Beck

Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, 2019

2018

Intruder alert! Optimization models for solving the mobile robot graph-clear problem.

Michael Morin, Margarita P. Castro, Kyle E. C. Booth, Tony T. Tran, Chang Liu, J. Christopher Beck

Constraints An Int. J., 2018

Compiling Optimal Numeric Planning to Mixed Integer Linear Programming.

Chiara Piacentini, Margarita P. Castro, André Augusto Ciré, J. Christopher Beck

Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018

Linear and Integer Programming-Based Heuristics for Cost-Optimal Numeric Planning.

Chiara Piacentini, Margarita P. Castro, André Augusto Ciré, J. Christopher Beck

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018