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

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.

Development of a Hybrid Machine Learning Model for Asphalt Pavement Temperature Prediction

“…This technique draws samples, and the following sample is based on the existing sample sequences of probabilistically related events to result in a solution within a reasonable period [45], [46]. This type of ML has the advantage of making reversible jumps because of its flexibility to include many possible moves based on the selection strategy compared to other schemes that rely on the indicator mix selections or diffusion processes [47]. The reversible jump is a tricky and timeconsuming mechanism of this technique for reversible engineering actions.…”

Adaptive General Search Framework for Games and Beyond

“…Automatic generation has been investigated to different extents and with different levels of generality for data processing algorithms [35], reinforcement learning [36], [37], and distributed algorithms for multi-agent systems [38]. However, not much work has been performed on automatic generation of search algorithms, despite the wide variety of real-world applications that might benefit from it [3], [4], [6]. Automatic generation has been explored also at a higher level.…”

“…Various applications of search algorithms can be found also in logistic [3] and robotics [65], [66]. Many more examples can be mentioned, including structural engineering [6], protecting natural resources from illegal extraction [67], forecasting financial volatility of assets [68], managing wildfires [69], improving computeraided retrosynthesis [70] and maximizing the performance of job scheduling heuristics [71]. Many more applications are being explored every day.…”

“…Search and planning have been identified among the core competences that an AGI should possess [2]. Moreover, we are currently facing the need to plan ahead in increasingly more complex situations, and search has shown to be successful in many applications that involve sequential decision making, such as logistics [3], health care [4], [5], and structural engineering [6]. This motivates the interest in investigating search algorithms form an AGI perspective.…”

Probabilistic Approach to Limit States of a Steel Dome

“…The first order reliability method (FORM) [ 5 , 6 , 7 ] and the second order reliability method (SORM) [ 8 , 9 , 10 , 11 ] are approximated approaches. Importance sampling [ 12 , 13 , 14 ], artificial intelligence [ 15 , 16 ], and the Monte Carlo method [ 17 , 18 , 19 ] are simulation approaches. A probabilistic approach makes it possible to provide a description that is more accurate and closer to the actual reality with respect to structure materials, geometric parameters, and loads.…”