Research And Implementation Of An Assisted Activity Planning System For Curing Internet Addiction Based On Dynamic Planning Algorithms

With the explosive growth of Internet, the Internet has become an indispensable part in our life. Now more and more people, especially the teenagers, have been addicted to the virtual network world and it is difficult for them to extricate themselves from the problem. The study on Internet Addiction has become one of the most concerned topics at home and abroad. At present, the scholar’s research on Internet addiction is limited to a single discipline and field. Perfect and specific plan is scarce. Therefore, this thesis proposes using dynamic planning algorithm to develop strategies and implements a system for curing Internet Addiction. The main contents are summarized as follows:Firstly, the comprehensive model is selected as theoretical guide. By analyzing theoretical models, the formation process of Internet Addiction is fully understood. Theoretical basis to solve the Internet Addiction can be found.Secondly, activity library for curing Internet Addiction is established. Those curing activities are extracted from Internet Addiction invention system, Internet Addiction treatment system, Internet Addiction transformation system. According to the type of Internet Addiction and occupation group, this thesis divides the extracted curing activities. Thus, the activity library for curing Internet Addiction is established.Thirdly, the constraint rules of curing activities are formulated. According to the overall requirements and specific arrangements for curing the Internet Addiction, the hard and soft constraints to plan the activity rationally are defined. This constraint rules define the score for each corresponding rules, and cumulate the conflict score throughout the activity. Moved by the cumulative score until the conflict score is zero, the optimal planning solution can be obtained.Fourthly, the curing Internet Addiction schedule is given. Tabu search and simulated annealing algorithms are used to plan curing activities. In the tabu search algorithm, based on tabu table, the activity plan can jump out of locally optimal solution and finally find the global optima to taboo the Internet Addiction curing activity. In simulated annealing algorithm, we firstly set up the initial temperature of curing activity. As the temperature is falling, the global optimal solution is found based on probabilistic jumping property random finding target function in the solution space. The performance test and compare for the two algorithms are performed by experiments. The results show that these two algorithms are effective for planning the curing activity.Fifthly, the planning system for curing Internet Addiction is designed and implemented. The patients input the Internet Addiction types and occupation. According to their preferences, we set the Internet Addiction curing activities. Based on the input information, the system will program dynamic and give a visual form of the Internet Addiction curing activity schedule to assist the patients to give up Internet Addiction.