12 citations · 32 across the 21 of their papers we have counts for
4 papers · 1 filter
Distributed Policy Gradient with Variance Reduction in Multi-Agent Reinforcement Learning
Xiaoxiao Zhao, Jinlong Lei, Li Li +1
This paper studies a distributed policy gradient in collaborative multi-agent reinforcement learning (MARL), where agents over a communication network aim to find the optimal polic…
Exploiting homogeneity for the optimal control of discrete-time systems: application to value iteration
Mathieu Granzotto, Romain Postoyan, Lucian Buşoniu +2
To investigate solutions of (near-)optimal control problems, we extend and exploit a notion of homogeneity recently proposed in the literature for discrete-time systems. Assuming t…
ObserveNet Control: A Vision-Dynamics Learning Approach to Predictive Control in Autonomous Vehicles
Cosmin Ginerica, Mihai Zaha, Florin Gogianu +3
A key component in autonomous driving is the ability of the self-driving car to understand, track and predict the dynamics of the surrounding environment. Although there is signifi…
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela Rosca +3
Most of the recent deep reinforcement learning advances take an RL-centric perspective and focus on refinements of the training objective. We diverge from this view and show we can…