3 papers
cs.CE2026
The Enhanced Physics-Informed Kolmogorov-Arnold Networks: Applications of Newton's Laws in Financial Deep Reinforcement Learning (RL) Algorithms
Trang Thoi, Hung Tran, Tram Thoi +1
Deep Reinforcement Learning (DRL), a subset of machine learning focused on sequential decision-making, has emerged as a powerful approach for tackling financial trading problems. I…
econ.EM2025
Equilibrium-Constrained Estimation of Recursive Logit Choice Models
Hung Tran, Tien Mai, Minh Hoang Ha
The recursive logit (RL) model provides a flexible framework for modeling sequential decision-making in transportation and choice networks, with important applications in route cho…
econ.EM2025
Constrained Recursive Logit for Route Choice Analysis
Hung Tran, Tien Mai, Minh Ha Hoang
The recursive logit (RL) model has become a widely used framework for route choice modeling, but it suffers from a key limitation: it assigns nonzero probabilities to all paths in…