The invention discloses a machine learning method for realizing ship anthropomorphic intelligent collision prevention decision. An analog source and an example source are generated by off-line artificial learning, and a collision prevention model for on-line acquiring new collision avoidance knowledge, and a database for storing ship parameters are constructed, and an automatic reasoning mechanism, a calculation unit and an evaluation system are designed. The collision prevention model and the automatic reasoning mechanism are used, knowledge discovery and approximate reinforcement learning strategies are realized through online machine learning, and new collision prevention knowledge is acquired, and a dynamic collision avoidance knowledge base is constructed. An inference engine is usedto invoke the ship parameters and the PIDVCA algorithm of the database through the automatic inference mechanism to realize the intelligent collision prevention decision of the machine. The machine iscapable of acquiring the information and the formalized collision prevention domain knowledge on site through the guidance of the automatic reasoning mechanism, is used to learn and solve new knowledge of collision prevention problems of any meeting scene, and has a perception target and a cognitive target to further formulate a scientific and reasonable collision prevention decision scheme, andfinally has a thinking mode for simulating and surpassing the human to solve complex collision prevention problems.