TY  - JOUR
A1  - Rossi, Leonardo
A1  - Winands, Mark H. M.
A1  - Butenweg, Christoph
ED  - Zhang, Jessica
T1  - Monte Carlo Tree Search as an intelligent search tool in structural design problems
JF  - Engineering with Computers : An International Journal for Simulation-Based Engineering
N2  - Monte Carlo Tree Search (MCTS) is a search technique that in the last decade emerged as a major breakthrough for Artificial Intelligence applications regarding board- and video-games. In 2016, AlphaGo, an MCTS-based software agent, outperformed the human world champion of the board game Go. This game was for long considered almost infeasible for machines, due to its immense search space and the need for a long-term strategy. Since this historical success, MCTS is considered as an effective new approach for many other scientific and technical problems. Interestingly, civil structural engineering, as a discipline, offers many tasks whose solution may benefit from intelligent search and in particular from adopting MCTS as a search tool. In this work, we show how MCTS can be adapted to search for suitable solutions of a structural engineering design problem. The problem consists of choosing the load-bearing elements in a reference reinforced concrete structure, so to achieve a set of specific dynamic characteristics. In the paper, we report the results obtained by applying both a plain and a hybrid version of single-agent MCTS. The hybrid approach consists of an integration of both MCTS and classic Genetic Algorithm (GA), the latter also serving as a term of comparison for the results. The study’s outcomes may open new perspectives for the adoption of MCTS as a design tool for civil engineers.
KW  - Monte Carlo Tree Search
KW  - Structural design
KW  - Artificial intelligence
KW  - Civil engineering
KW  - Genetic algorithm
Y1  - 2022
U6  - http://dx.doi.org/10.1007/s00366-021-01338-2
SN  - 1435-5663
SN  - 0177-0667
VL  - 38
IS  - 4
SP  - 3219
EP  - 3236
PB  - Springer Nature
CY  - Cham
ER  -