1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
Gaussian-Mixture-Model Q-Functions for Policy Iteration in Reinforcement Learning
Minh Vu, Konstantinos Slavakis
Unlike their conventional use as estimators of probability density functions in reinforcement learning (RL), this paper introduces a novel function-approximation role for Gaussian…
A Multi-Criterion Approach to Smart EV Charging with CO2 Emissions and Cost Minimization
Giuseppe C. Calafiore, Luca Ambrosino, Khai Manh Nguyen +3
We study carbon-aware smart charging in a fossil-dominated grid by coupling a simplified hydro-thermal-renewable dispatch model with a tractable linear charging scheduler. The case…
Online reinforcement learning via sparse Gaussian mixture model Q-functions
Minh Vu, Konstantinos Slavakis
This paper introduces a structured and interpretable online policy-iteration framework for reinforcement learning (RL), built around the novel class of sparse Gaussian mixture mode…
Nonparametric Bellman Mappings for Value Iteration in Distributed Reinforcement Learning
Yuki Akiyama, Konstantinos Slavakis
This paper introduces novel Bellman mappings (B-Maps) for value iteration (VI) in distributed reinforcement learning (DRL), where agents are deployed over an undirected, connected…