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).
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinforcement learning) in the context of quantitative trading
AI4U is a multi-engine plugin (Unity and Godot) that allows you to specify agents with reinforcement learning visually. Non-Player Characters (NPCs) of games can be designed using ready-made components. 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 Articial Intelligence community in general.
Environment
1.6.5allBug description
How to reproduce
When using the
MultifolderWithCacheclass combin