Improve agent score comprehensibility

[rakow]

In complex scenarios, it can be quite difficult to understand why agents chose a certain plan over another. We may see the total score at the end, but may not be aware what led to that score. In my opinion, a good understanding about all separate factors in the scoring function is very useful, especially when calibrating or debugging scenarios.

This PR tries to address this by adding a explainScore(StringBuilder out) method to the scoring interface. By implementing this method, scoring functions may write out individual components of the scoring process. These score explanations are attached as attributes to a plan if ScoringConfigGroup.writeScoreExplanations is enabled. The implementation tries to not cause any overhead if the feature is disabled, in this case no strings are constructed. In this PR the functionality has been implemented for the default CharyparNagelScoring. Scores can be slightly different now at the last significant digits (~10e-15), because the order of floating point operations is now different.

Feedback for the implementation or the idea in general is very welcome.