Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-playing bots or solving sequential decision problems. The method relies on intelligent tree search that balances exploration and exploitation. MCTS performs random sampling in the form of simulations and stores statistics of actions to make more educated choices in each subsequent iteration. The method has become a state-of-the-art technique for combinatorial games. However, in more complex games (e.g. those with a high branching factor or real-time ones) as well as in various practical domains (e.g. transportation, scheduling or security) an efficient MCTS application often requires its problem-dependent modification or integration with other techniques. Such domain-specific modifications and hybrid approaches are the main focus of this survey. The last major MCTS survey was published in 2012. Contributions that appeared since its release are of particular interest for this review.
Magnetic fluid hyperthermia (MFH) is a minimally invasive procedure that destroys cancer cells. It is based on a superparamagnetic heat phenomenon and consists in feeding a ferrofluid into a tumor, and then applying an external electromagnetic field, which leads to apoptosis. The strength of the magnetic field, optimal dose of the ferrofluid, the volume of the tumor and the safety standards have to be taken into consideration when MFH treatment is planned. In this study, we have presented the novel complementary investigation based both on the experiments and numerical methodology connected with female breast cancer. We have conducted experiments on simplified female breast phantoms with numerical analysis and then we transferred the results on an anatomically-like breast model.
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