1 research outputs found
Surprise search : beyond objectives and novelty
Grounded in the divergent search paradigm and inspired
by the principle of surprise for unconventional discovery
in computational creativity, this paper introduces surprise
search as a new method of evolutionary divergent search.
Surprise search is tested in two robot navigation tasks and
compared against objective-based evolutionary search and
novelty search. The key findings of this paper reveal that
surprise search is advantageous compared to the other two
search processes. It outperforms objective search and it is
as efficient as novelty search in both tasks examined. Most
importantly, surprise search is, on average, faster and more
robust in solving the navigation problem compared to ob-
jective and novelty search. Our analysis reveals that sur-
prise search explores the behavioral space more extensively
and yields higher population diversity compared to novelty
search.This work has been supported in part by the FP7 Marie
Curie CIG project AutoGameDesign (project no: 630665).
The authors would also like to thank Dora Lee Borg for
initial implementations of the algorithm.peer-reviewe