Code and Data for paper: Bayesian-Belief Direct Policy Search for Adaptive Water Supply Planning with Endogenous Learning
Zhang, Mofan; Lickley, Megan; ZANIOLO, MARTA; Nellikkattil, Arjun; Fletcher, Sarah;
Code and Data for paper: Bayesian-Belief Direct Policy Search for Adaptive Water Supply Planning with Endogenous Learning
This record archives the code (and supporting data) used in Bayesian-Belief Direct Policy Search for Adaptive Water Supply Planning with Endogenous Learning.The repository includes: (i) policy training scripts (Bayesian DPS and standard DPS), (ii) simulation model and experiment configuration files, and (iii) scripts to reproduce the main figures and tables in the manuscript and Supporting Information. How to reproduce: Install dependencies (see Readme/Requirements). Run main_par.py to generate experiments.
- Duke University United States
- Stanford University United States
- Georgetown University United States
reinforcement learning, adaptive planning, bayesian learning, bayesian decision making
reinforcement learning, adaptive planning, bayesian learning, bayesian decision making
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selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
Average
Average
Average