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AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Control
The first attention model is introduced to handle different numbers of roads-lanes; and the second attention model is intended for enabling decision-making with any number of phases in an intersection.
A Review of Cooperative Multi-Agent Deep Reinforcement Learning
Due to the recent success of MARL in real-world applications, we assign a section to provide a review of these applications and corresponding articles.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Zeroth Order Nonconvex Multi-Agent Optimization over Networks
In this paper, we consider distributed optimization problems over a multi-agent network, where each agent can only partially evaluate the objective function, and it is allowed to exchange messages with its immediate neighbors.
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
In this paper we consider nonconvex optimization and learning over a network of distributed nodes.
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization
We study a stochastic and distributed algorithm for nonconvex problems whose objective consists of a sum of $N$ nonconvex $L_i/N$-smooth functions, plus a nonsmooth regularizer.
