Segment Tree( Assign- Sum) Algorithm

construct skill trees (CST) is a hierarchical reinforcement learning algorithm which can construct skill trees from a set of sample solution trajectories obtained from demonstration. CST uses an incremental MAP(maximum a posteriori) change point detection algorithm to segment each demonstration trajectory into skills and integrate the outcomes into a skill tree.

Segment Tree( Assign- Sum) source code, pseudocode and analysis

Then, CST calculate the probability of the changepoint at time J with model q, The change-point detection algorithm is used to segment data into skills and uses the sum of discounted reward R t { \displaystyle R_{t}^ { } } as the target regression variable.