4 papers
EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning
Parvin Malekzadeh, Zissis Poulos, Jacky Chen +2
Recent advancements in Distributional Reinforcement Learning (DRL) for modeling loss distributions have shown promise in developing hedging strategies in derivatives markets. A com…
A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning
Parvin Malekzadeh, Konstantinos N. Plataniotis, Zissis Poulos +1
Distributional Reinforcement Learning (RL) estimates return distribution mainly by learning quantile values via minimizing the quantile Huber loss function, entailing a threshold p…
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
Exploration is a significant challenge in practical reinforcement learning (RL), and uncertainty-aware exploration that incorporates the quantification of epistemic and aleatory un…
Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation
Mohammad Salimibeni, Arash Mohammadi, Parvin Malekzadeh +1
Distributed Multi-Agent Reinforcement Learning (MARL) algorithms has attracted a surge of interest lately mainly due to the recent advancements of Deep Neural Networks (DNNs). Conv…