mctreesearch4j: A Monte Carlo Tree Search Implementation for the JVM

We introduce mctreesearch4j, a Monte Carlo Tree Search (MCTS) implementation written as a standard JVM (Java Virtual Machine) library following key object oriented programming design principles. This modular and extensibile implementation of MCTS provides a powerful tool to enable the discovery of approximate solutions to complex planning problems via rapid experimentation. mctreesearch4j utilizes class inheritance and generic types to standardize custom algorithm definitions. In addition, key class abstractions are designed for the library to flexibly adapt to any well-defined Markov Decision Process (MDP) or turn-based adversarial games. Furthermore, mctreesearch4j is capable of customization across a variety of MDP domains, consequently enabling the adoption of MCTS heuristics and customization into the core library with ease.