ai-economist
maro
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| ai-economist | maro | |
|---|---|---|
| 5 | 9 | |
| 1,060 | 814 | |
| - | 2.6% | |
| 0.0 | 3.5 | |
| 8 months ago | 2 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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.
ai-economist
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Agent-based modeling in applied economics?
3 Area of Reinforcement learning, in particular, has demonstrated impressive breakthroughs recently. There were attempts to apply it to economic policy planning and finance
- "The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning", Zheng et al 2021 {Salesforce}
- How to assemble the The AI Economist program in python ?
- IA economista comparou modelos de livre mercado, de taxação maior sobre os ricos, e seu próprio modelo de desenvolvimento para descobrir qual deles melhor promove alta produtividade e igualdade social. Resultado: livre mercado é o pior modelo, e a IA se saiu melhor que o modelo proposto por Saez
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Improving Equality and Productivity with AI-Driven Tax Policies
They're also on Github -> https://github.com/salesforce/ai-economist
maro
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Headstart for multi-container optimization problem.
Yes, I have actually. Some of them which i could find out were: https://github.com/tryton/tryton/tree/main https://pypi.org/project/pyShipping-python3/ https://github.com/microsoft/maro https://github.com/yat-co/yat-trailer-loading https://github.com/duyet/openerp-6.1.1
- maro: NEW Deep Learning And Reinforcement Learning - star count:609.0
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What's the outlook of Reinforcement Learning?
As far as current SOTA applications, you can just Google it and find plenty of examples of RL being used outside the realm of games. Video/board games offer a nice domain for research in RL, but the underlying algorithms can be (and have been) applied to plenty of domains outside of this. A big one, currently, is robotics. Another example is resource optimization, which is probably currently being developed, if not used, in a lot of technical domains. As u/daddabarba pointed out, RL can also be used in other areas of AI, like text generation.
What are some alternatives?
Mava - 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
openerp-6.1.1
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
agents-aea - A framework for autonomous economic agent (AEA) development
robo-gym - An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots.
VMAgent - Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.
0xDeCA10B - Sharing Updatable Models (SUM) on Blockchain
pyEnigma - Python Enigma cypher machine simulator.
MLflow - Open source platform for the machine learning lifecycle
blender-quadcopter-fpv - Quadcopter FPV Simulator for blender to capture epic footage
tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
palletier - Palletier is a Python implementation of the solution for the distributer's pallet packing problem