Search Results for "edmonds-karp algorithm implementation in python"
Sort By:
Showing 4 open source projects for "edmonds-karp algorithm implementation in python"
View related business solutions-
Your top-rated shield against malware and online scams | Avast Free AntivirusOur antivirus software scans for security and performance issues and helps you to fix them instantly. It also protects you in real time by analyzing unknown files before they reach your desktop PC or laptop — all for free.
-
Simplify IT and security with a single endpoint management platformNinjaOne automates the hardest parts of IT, delivering visibility, security, and control over all endpoints for more than 20,000 customers. The NinjaOne automated endpoint management platform is proven to increase productivity, reduce security risk, and lower costs for IT teams and managed service providers. The company seamlessly integrates with a wide range of IT and security technologies. NinjaOne is obsessed with customer success and provides free and unlimited onboarding, training, and support.
-
1
LightZero
[NeurIPS 2023 Spotlight] LightZero
LightZero is an efficient, scalable, and open-source framework implementing MuZero, a powerful model-based reinforcement learning algorithm that learns to predict rewards and transitions without explicit environment models. Developed by OpenDILab, LightZero focuses on providing a highly optimized and user-friendly platform for both academic research and industrial applications of MuZero and similar algorithms. -
2
AI4U
Multi-engine plugin to specify agents with reinforcement learning
AI4U is a multi-engine plugin (Godot and Unity) that allows you to design Non-Player Characters (NPCs) of games using an agent abstraction. In addition, AI4U has a low-level API that allows you to connect the agent to any algorithm made available in Python by the reinforcement learning community specifically and by the Artificial Intelligence community in general. Reinforcement learning promises to overcome traditional navigation mesh mechanisms in games and to provide more autonomous... -
3
CleanRL
High-quality single file implementation of Deep Reinforcement Learning
CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should... -
4
Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
- Previous
- You're on page 1
- Next
