15 citations · 19 across the 8 of their papers we have counts for
4 papers · 2 filters
A hybrid classical-quantum approach to highly constrained Unit Commitment problems
Bruna Salgado, André Sequeira, Luis Paulo Santos
The unit commitment (UC) problem stands as a critical optimization challenge in the electrical power industry. It is classified as NP-hard, placing it among the most intractable pr…
Trainability issues in quantum policy gradients
André Sequeira, Luis Paulo Santos, Luis Soares Barbosa
This research explores the trainability of Parameterized Quantum circuit-based policies in Reinforcement Learning, an area that has recently seen a surge in empirical exploration.…
On Quantum Natural Policy Gradients
André Sequeira, Luis Paulo Santos, Luis Soares Barbosa
This research delves into the role of the quantum Fisher Information Matrix (FIM) in enhancing the performance of Parameterized Quantum Circuit (PQC)-based reinforcement learning a…
VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainability
Rodrigo Coelho, André Sequeira, Luís Paulo Santos
Reinforcement Learning (RL) consists of designing agents that make intelligent decisions without human supervision. When used alongside function approximators such as Neural Networ…