TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Hagg, Alexander
A1  - Asteroth, Alexander
A1  - Bäck, Thomas
T1  - Modeling User Selection in Quality Diversity
T2  - GECCO '19: Genetic and Evolutionary Computation Conference, Prague, Czech Republic, July 13-17, 2019
N2  - The initial phase in real world engineering optimization and design is a process of discovery in which not all requirements can be made in advance, or are hard to formalize. Quality diversity algorithms, which produce a variety of high performing solutions, provide a unique chance to support engineers and designers in the search for what is possible and high performing. In this work we begin to answer the question how a user can interact with quality diversity and turn it into an interactive innovation aid. By modeling a user's selection it can be determined whether the optimization is drifting away from the user's preferences. The optimization is then constrained by adding a penalty to the objective function. We present an interactive quality diversity algorithm that can take into account the user's selection. The approach is evaluated in a new multimodal optimization benchmark that allows various optimization tasks to be performed. The user selection drift of the approach is compared to a state of the art alternative on both a planning and a neuroevolution control task, thereby showing its limits and possibilities.
SN  - 978-1-4503-6111-8
SB  - 978-1-4503-6111-8
U6  - https://doi.org/10.1145/3321707.3321823
DO  - https://doi.org/10.1145/3321707.3321823
AX  - 1907.06912
SP  - 116
EP  - 124
PB  - ACM
CY  - New York, NY, USA
ER  -