2 papers
cs.LG2026
Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
Matias Alvo, Daniel Russo, Yash Kanoria
We study reinforcement learning in hybrid discrete-continuous action spaces, such as settings where the discrete component selects a regime (or index) and the continuous component…
cs.LG2025
Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization
Matias Alvo, Daniel Russo, Yash Kanoria +1
We argue that inventory management presents unique opportunities for the reliable application of deep reinforcement learning (DRL). To enable this, we emphasize and test two comple…