20 citations · 29 across the 12 of their papers we have counts for
5 papers · 1 filter
SAVGO: Learning State-Action Value Geometry with Cosine Similarity for Continuous Control
Stavros Orfanoudakis, Pedro P. Vergara
While representation and similarity learning have improved the sample efficiency of Reinforcement Learning (RL), they are rarely used to shape policy updates directly in the action…
Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
Shuyi Gao, Stavros Orfanoudakis, Shengren Hou +2
Optimal dispatch of energy storage systems (ESSs) in distribution networks involves jointly improving operating economy and voltage security under time-varying conditions and possi…
Flow Matching Policy Optimization with Mirror Descent and Entropy Constraints
Ting Gao, Stavros Orfanoudakis, Nan Lin +3
Balancing policy expressiveness with the exploration-exploitation trade-off is a core challenge in online Reinforcement Learning (RL). While Stochastic Differential Equation (SDE)-…
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
Stavros Orfanoudakis, Nanda Kishor Panda, Peter Palensky +1
Reinforcement Learning (RL) methods used for solving real-world optimization problems often involve dynamic state-action spaces, larger scale, and sparse rewards, leading to signif…
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
Nan Lin, Stavros Orfanoudakis, Nathan Ordonez Cardenas +2
Accurate and efficient power flow (PF) analysis is crucial in modern electrical networks' operation and planning. Therefore, there is a need for scalable algorithms that can provid…