Action-branching-agents Alternatives
Similar projects and alternatives to action-branching-agents based on common topics and language
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pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Deep-Reinforcement-Learning-in-Large-Discrete-Action-Spaces
PyTorch implementation of the paper "Deep Reinforcement Learning in Large Discrete Action Spaces" (Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin).
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action-branching-agents reviews and mentions
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Large Action Spaces
Exactly, multiple action heads. There are some works that try this for DQN as https://arxiv.org/abs/1711.08946. However, i have not tried since I tend to prefer actor-critic methods.
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(Newbie question)How to solve using reinforcement learning 2x2 rubik's cube which has 2^336 states without ValueError?
That's a larger number than the number of atoms in the Universe. You need some kind of branching to limit the actions. Check out: https://github.com/atavakol/action-branching-agents
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atavakol/action-branching-agents is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of action-branching-agents is Python.
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