Beijing Worker''s Gymnasium-Project Case-COOLNIO

It is also a key project in Beijing''s sports development planning and cultivating the construction of an international consumption center city.

Welcome to gym-anm! — gym-anm v1 documentation

The flexibility of gym-anm, with its different customizable components, makes it a suitable framework to model a wide range of ANM tasks, from simple ones that can be used for educational purposes, to

CYB453 Group Project Week 2: SOHO Network Infrastructure Proposal

This device is a simple plug-in solution for extending your network to allow communication between multiple devices. Tech specs include ethernet switching capabilities 802 QoS, 8 queues; 802 VLAN

Gym-ANM: Reinforcement learning environments for active network

Active network management (ANM) of electricity distribution networks include many complex stochastic sequential optimization problems. These problems need to be solved for

ns3-gym: Integrating OpenAI Gym with ns-3 | PDF | Computer Network

Integrating OpenAI Gym with ns-3 via the ns3-gym framework offers the significant benefit of allowing researchers to apply reinforcement learning (RL) to network simulation environments in a unified

Gymnasium Documentation

Gymnasium is a maintained fork of OpenAI''s Gym library. The Gymnasium interface is simple, pythonic, and capable of representing general RL problems, and has a migration guide for old Gym environments:

What is the grid-connected cabinet, how to choose the suitable grid

According to the investment budget of the project, the model and configuration of the grid-connected cabinet should be reasonably selected to avoid excessive pursuit of high-end

China Electric power, China Low Voltage Switchgear, Medium Voltage

The rated current of the low-voltage power distribution cabinet is AC 50Hz, and the power distribution system with a rated voltage of 380v is used for power conversion and control of power, lighting and

Deep Q-Network (DQN) for LunarLander-v3

The goal of this project is to train an agent using the DQN algorithm to land a spacecraft safely on a designated landing pad in the "LunarLander-v3" environment.

7-Gym-solution.ipynb

On colab, gym cannot open graphical windows for visualizing the environments, as it is not possible in the browser. We will see a workaround allowing to produce videos.