In this paper, we present prisma-v2, a new release of prisma, a Packet Routing Simulator for
Multi-Agent Reinforcement Learning. prisma-v2 brings a new set of features. First, it allows …

In this paper, we present PRISMA: Packet Routing Simulator for Multi-Agent Reinforcement
Learning. To the best of our knowledge, this is the first tool specifically conceived to develop …

OpenAI Gym is a toolkit for reinforcement learning (RL) research. It includes a large number
of well-known problems that expose a common interface allowing to directly compare the …

Packet Routing has been investigated intensively in computer networking with numerous
existing solutions. However, with the increasing usage of distributed networks that have …

Recently, we have seen a boom of attempts to improve the operation of networking protocols
using machine learning techniques. The proposed reinforcement learning (RL) based …

Multi-Agent Reinforcement Learning (MARL) is nowadays widely used to solve real-world
and complex decisions in various domains. While MARL can be categorized into …

In recent years, several works have studied Multi-Agent Deep Reinforcement Learning for
the Distributed Packet Routing problem, with promising results in various scenarios where …

Recent game-theoretic approaches to con-structing overlay network topologies have not
been scalable. This paper introduces a machine learning approach to constructing overlay …

XLRON: Accelerated Reinforcement Learning Environments for Optical Networks Page 1
XLRON: Accelerated Reinforcement Learning Environments for Optical Networks Michael …

Reinforcement Learning (RL) is leading to important breakthroughs in several areas (eg, self-
driving vehicles, robotics, and network automation). Part of its success is due to the …