refine_plan.learning.option_learning
Functions for processing datsets and learning DBNs.
Author: Charlie Street Owner: Charlie Street
Module Contents
Functions
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Processes a mongodb collection into a yaml dataset for DBN learning. |
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Learn a set of DBNs representing options. |
- refine_plan.learning.option_learning.mongodb_to_yaml(connection_str, db_name, collection_name, sf_list, out_file)
Processes a mongodb collection into a yaml dataset for DBN learning.
- Parameters:
connection_str – The mongodb connection string
db_name – The Mongo database name
collection_name – The collection within the database
sf_list – The list of state factors to expect in the MongoDB
out_file – The path for the yaml file
- refine_plan.learning.option_learning.learn_dbns(dataset_path, output_dir, sf_list)
Learn a set of DBNs representing options.
The dataset should be a dictionary from options to a dictionary with two keys: ‘transition’ and ‘reward’. In ‘transition’ there should be a dictionary with keys sf0 and sft for each state factor sf. At each of these keys is a list of data. In ‘reward’ there should be a dictionary with keys sf for each state factor sf, and ‘r’ to represent the reward. At each of these keys is a list of data
- Parameters:
dataset_path – A yaml file containing the dataset.
output_dir – The output directory for the DBNs.
sf_list – The list of state factors we expect to see in the dataset