maro VS pyEnigma

Compare maro vs pyEnigma and see what are their differences.

maro

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems. (by microsoft)

pyEnigma

Python Enigma cypher machine simulator. (by cedricbonhomme)
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maro pyEnigma
9 1
818 64
2.2% -
3.5 6.3
3 months ago about 1 month ago
Python Python
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

maro

Posts with mentions or reviews of maro. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.

pyEnigma

Posts with mentions or reviews of pyEnigma. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-28.

What are some alternatives?

When comparing maro and pyEnigma you can also consider the following projects:

openerp-6.1.1

bruteforce-enigma - A tool for cracking and bruteforcing Enigma ciphers.

agents-aea - A framework for autonomous economic agent (AEA) development

gym-mtsim - A general-purpose, flexible, and easy-to-use simulator alongside an OpenAI Gym trading environment for MetaTrader 5 trading platform (Approved by OpenAI Gym)

VMAgent - Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.

habitat-api - A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators. [Moved to: https://github.com/facebookresearch/habitat-lab]

ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

holodeck - High Fidelity Simulator for Reinforcement Learning and Robotics Research.

palletier - Palletier is a Python implementation of the solution for the distributer's pallet packing problem

habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.

blender-quadcopter-fpv - Quadcopter FPV Simulator for blender to capture epic footage

ELM327-emulator - ELM327 Emulator for testing software interfacing OBDII via ELM327 adapter supporting multi-ECU simulation