TY - GEN
T1 - Interactive Evolution of Complex Behaviours Through Skill Encapsulation
AU - González de Prado Salas, Pablo
AU - Risi, Sebastian
PY - 2017
Y1 - 2017
N2 - Human-based computation (HBC) is an emerging research area in which humans and machines collaborate to solve tasks that neither one can solve in isolation. In evolutionary computation, HBC is often realized through interactive evolutionary computation (IEC), in which a user guides evolution by iteratively selecting the parents for the next generation. IEC has shown promise in a variety of different domains, but evolving more complex or hierarchically composed behaviours remains challenging with the traditional IEC approach. To overcome this challenge, this paper combines the recently introduced ESP (encapsulation, syllabus and pandemonium) algorithm with IEC to allow users to intuitively break complex challenges into smaller pieces and preserve, reuse and combine interactively evolved sub-skills. The combination of ESP principles with IEC provides a new way in which human insights can be leveraged in evolutionary computation and, as the results in this paper show, IEC-ESP is able to solve complex control problems that are challenging for a traditional fitness-based approach.
AB - Human-based computation (HBC) is an emerging research area in which humans and machines collaborate to solve tasks that neither one can solve in isolation. In evolutionary computation, HBC is often realized through interactive evolutionary computation (IEC), in which a user guides evolution by iteratively selecting the parents for the next generation. IEC has shown promise in a variety of different domains, but evolving more complex or hierarchically composed behaviours remains challenging with the traditional IEC approach. To overcome this challenge, this paper combines the recently introduced ESP (encapsulation, syllabus and pandemonium) algorithm with IEC to allow users to intuitively break complex challenges into smaller pieces and preserve, reuse and combine interactively evolved sub-skills. The combination of ESP principles with IEC provides a new way in which human insights can be leveraged in evolutionary computation and, as the results in this paper show, IEC-ESP is able to solve complex control problems that are challenging for a traditional fitness-based approach.
KW - Human-based computation
KW - Interactive evolutionary computation
KW - ESP algorithm
KW - Hierarchical task decomposition
KW - Evolutionary control problems
KW - Human-based computation
KW - Interactive evolutionary computation
KW - ESP algorithm
KW - Hierarchical task decomposition
KW - Evolutionary control problems
U2 - 10.1007/978-3-319-55849-3_55
DO - 10.1007/978-3-319-55849-3_55
M3 - Article in proceedings
SN - 978-3-319-55848-6
T3 - Lecture Notes in Computer Science
SP - 853
EP - 869
BT - Applications of Evolutionary Computation. EvoApplications 2017
A2 - Squillero, Giovanni
A2 - Sim, Kevin
PB - Springer
ER -