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* [[Katsuki Ohto]], [[Tetsuro Tanaka]] ('''2016'''). ''Application of Monte Carlo Tree Search to Curling AI''. [[Conferences#GPW21|21st Game Programming Workshop]]
* [[Maciej Świechowski]], [[Jacek Mańdziuk]] ('''2016'''). ''A Hybrid Approach to Parallelization of Monte Carlo Tree Search in General Game Playing''. [https://www.springer.com/de/book/9783319301648 Challenging Problems and Solutions in Intelligent Systems], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [[S. Ali Mirsoleimani]], [[Aske Plaat]], [[Jaap van den Herik]], [[Jos Vermaseren]] ('''2016'''). ''A New Method for Parallel Monte Carlo Tree Search''. [https://arxiv.org/abs/1605.04447 arXiv:1605.04447] » [[Parallel Search]]
'''2017'''
* [[Dap Hartmann]] ('''2017'''). ''Let's Catch the Train to Monte-Carlo''. [[ICGA Journal#39_1|ICGA Journal, Vol. 39, No. 1]], Review on [[Hendrik Baier#PhD|Hendrik Baier's Ph.D. thesis]]
* [[S. Ali Mirsoleimani]], [[Aske Plaat]], [[Jaap van den Herik]], [[Jos Vermaseren]] ('''2017'''). ''Structured Parallel Programming for Monte Carlo Tree Search''. [https://arxiv.org/abs/1704.00325 arXiv:1704.00325]
* [[Katsuki Ohto]], [[Tetsuro Tanaka]] ('''2017'''). ''A Curling Agent Based on the Monte-Carlo Tree Search Considering the Similarity of the Best Action among Similar States''. [[Advances in Computer Games 15]]
* [[Naoki Mizukami]], [[Jun Suzuki]], [[Hirotaka Kameko]], [[Yoshimasa Tsuruoka]] ('''2017'''). ''Exploration Bonuses Based on Upper Confidence Bounds for Sparse Reward Games''. [[Advances in Computer Games 15]]
