Merged
Conversation
…gement to use true incremental scoring without reinserting/retracting all facts on each delta update)
… truly incremental score calculation! (TODO: reimplement greynet in Rust)
…ems without order planning. TODO: implement Chained Variables for problems like TSP, VRP, etc
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
*) GreyNet implementation. GreyNet is the the rule-engine, that allows true incremental estimation of constraints satisfaction. To understand more, see the docs in greyjack/score_calculation/greynet/docs.
*) A lot of examples for GreyNet
*) GreyNet score calculators for NQueens, CloudBalancing.
*) Note: currently GreyNet is entirely written in Python. I hope, that after reimplementation in Rust, it will completely outperform the pseudo incremental scoring mechanism, especially on really big datasets.