Expected flow networks in stochastic environments and two-player zero-sum games

arXiv:2310.02779 · cs.LG, cs.GT · Submitted 2023-10-04 · Read on arXiv

cs.LG, cs.GT

Submitted: 2023-10-04

Updated: 2026-08-31

Code: https://github.com/GFNOrg/AdversarialFlowNetworks

Terminology

• Reward Function — 12× in this paper · explained in 2 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• International Conference on Machine Learning — 5× in this paper
• Actor — 3× in this paper · explained in 3 episodes
• Generative Modeling — 3× in this paper · explained in 3 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Credit assignment — 2× in this paper · explained in 3 episodes
• International Conference on Learning Representations — 2× in this paper
• Pruning — 2× in this paper · explained in 4 episodes
• alpha — 2× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Algorithmic Improvements — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Uncertainty in Artificial Intelligence — 1× in this paper

Sources

• Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
• Thompson sampling for improved exploration in GFlowNets
• A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
• Distributional GFlowNets with Quantile Flows

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