Monte Carlo Tree Search as an intelligent search tool in structural design problems

L. Rossi*, M.H.M. Winands, C. Butenweg

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)3219–3236
Number of pages18
JournalEngineering with Computers
Volume38
Issue number4
Early online date26 Feb 2021
DOIs
Publication statusPublished - Aug 2022

Keywords

  • Artificial intelligence
  • Civil engineering
  • Genetic algorithm
  • Monte Carlo Tree Search
  • Reinforced concrete buildings
  • Structural design
  • artificial intelligence
  • civil engineering
  • genetic algorithm
  • monte carlo tree search
  • reinforced concrete buildings
  • structural design
  • GO
  • ARTIFICIAL NEURAL-NETWORKS
  • GAME

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