Jacob F. Pettit

According to our database, Jacob F. Pettit authored at least 5 papers between 2019 and 2025.

Collaborative distances:

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

2025

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics.

Conor F. Hayes, Felipe Leno da Silva, Jiachen Yang, T. Nathan Mundhenk, Chak Shing Lee, Jacob F. Pettit, Claudio Santiago, Sookyung Kim, Joanne Taery Kim, Ignacio Aravena Solis, Ruben Glatt, Andre R. Goncalves, Alexander Ladd, Ahmet Can Solak, Thomas Desautels, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela

CoRR, May, 2025

DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces.

Jacob F. Pettit, Chak Shing Lee, Jiachen Yang, Alex Ho, Daniel M. Faissol, Brenden K. Petersen, Mikel Landajuela

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2021

Improving exploration in policy gradient search: Application to symbolic optimization.

Mikel Landajuela, Brenden K. Petersen, Soo K. Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol

CoRR, 2021

Discovering symbolic policies with deep reinforcement learning.

Mikel Landajuela, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol

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

2019

Increasing performance of electric vehicles in ride-hailing services using deep reinforcement learning.

Jacob F. Pettit, Ruben Glatt, Jonathan R. Donadee, Brenden K. Petersen

CoRR, 2019