Computerized Interactive Gaming via Supporting Vector Machines

Computerized interactive gaming requires automatic processing of large volume of randomdata produced by players on spot, such as shooting, football kicking, and boxing. This paper describes a supporting vector machine-based artificial intelligence algorithm as one of the possible solutions to the problem of random data processing and the provision of interactive indication for further actions. In comparison with existing techniques, such as rule-based and neural networks, and so forth, our SVM-based interactive gaming algorithm has the features of (i) high-speed processing, providing instant response to the players, (ii) winner selection and control by one parameter, which can be predesigned and adjusted according to the needs of interaction and game design or specific level of difficulties, and (iii) detection of interaction points is adaptive to the input changes, and no labelled training data is required. Experiments on numerical simulation support that the proposed algorithm is robust to random noise, accurate in picking up winning data, and convenient for all interactive gaming designs.

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