Users' Cognition Principles In Interactive Genetic Algorithms And Their Applications

Interactive genetic algorithm (IGA) combines human's intelligence with genetic algorithm (GA) together to solve problems in which their performance indices are implicit or difficult to be expressed by explicit functions. When IGA makes use of human's intelligence, it has to consider human's limitations. For example, the population size and the evolutionary generation should not be more than 20 for human's fatigue and limitation of cognition ability. Therefore, the performances of IGA are often restricted by small population size and a few evolutionary generations. Many researchers have studied methods to improve IGA's performances. Almost all of the methods are based on the information of the user's preference. In fact, a user's preference is the synthesis of different kinds of cognitions. So it is important to study on the principles of the user's cognition, which will be helpful not only to get the information of the user's preference, but also to study the methods to improve IGA's performance. But it is regret that there have been few researches on the principles of the user's cognition.This dissertation mainly focused on the principles of the user's cognition in IGA. Firstly, the principle of the user's reference cognition in IGA is studied. Also, this dissertation addresses its influence on the convergence of IGA. The strong condition and weak condition of convergence of IGA with fitness noise are given. Secondly, the principles of the user's rationality cognition are studied. Based on the principles, we find that the ability for the user to keep rational state is a sufficient condition for the convergence of IGA. In order to help the user to keep rational state, the maximum generations should be different for different methods of fitness assignment. Based on this viewpoint, the maximum generation problem was studied. Thirdly, the principle of users'uncertainty cognition is studied. In order to identify the uncertainty information, the method of quantities identification is given. Then the method to abstract users'preference knowledge from certainty information is given and the method to express and update the user's preference knowledge is studied. Fourthly, the principle of the user's selection attention cognition is studied. In order to get the knowledge of the user's attention, we consider two optimization problems: (1) the maximum number of gene sense units that attract the user's attention with small population size and (2) the minimum size of population in which the knowledge of the user's attention to all the gene sense units can be deduced. In order to make use of the above knowledge, the special method to initialize population and the method to track the attention fluctuation are given. Finally, we address the realization of IGA and the realization of 3 dimension cartoon characteristics design which is based on IGA is given.The studies on the principles of the user's cognition in IGA not only enrich the basic theory of IGA, but also provide necessary instruction for IGA application.