Multiagent Libraries

5 Components & Libraries

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Multiagent Libraries

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, …

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

A parallel framework for population-based multi-agent reinforcement learning.

MALib is a parallel framework of population-based learning nested with reinforcement learning methods, such as Policy Space Response Oracle, Self-Play, and Neural Fictitious Self-Play. MALib provides…

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

We provide here a suite of Python examples that walk you through concepts in: Classical & Deep Reinforcement Learning Basic & Advanced Machine Learning Anson Wong

A framework to empower forecasting using Large Language Models (LLMs)

Given the stochastic nature of large language models, individual data points may vary. However, if a sufficient number of agents are employed, the generated models can effectively support comparative…

Related tags

semi-supervised-learning

vector

unsupervised-learning

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consists