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

Understand

Generative flow networks (GFlowNets) are sequential sampling models trained to match a given distribution.

• GFlowNets have been successfully applied to various structured object generation tasks, sampling a diverse set of high-reward objects quickly.
• We propose expected flow networks (EFlowNets), which extend GFlowNets to stochastic environments.
• We show that EFlowNets outperform other GFlowNet formulations in stochastic tasks such as protein design.