Modeling and simulating inhibitory mechanisms in mental image reinterpretation : towards cooperative human-computer creativity

With the accelerating development of computer and software technology, human-computer cooperation issues are becoming more and more centered on the human user's abilities and weaknesses. The cognitive characteristics of visual communication and reasoning, and how these affect the way users take advantage of the richness of visually represented information comprise one area which needs to be further explored within this context.The work reported in this thesis aims to identify cognitive mechanisms which might inhibit the creative interpretation of visual information, and thereby indicate which aspects of visual creativity may benefit from support in a cooperative human-computer system.We approached this problem by initially focusing on one central mechanism, selective attention, with an analysis of its constraining role in mental image reinterpretation. From this kernel, a partial model of mental image reinterpretation was developed. Given this framework, a family of related, yet, at a detailed level contradictory cognitive models was simulated to determine which model components contributed in what way to overall model performance. Model performance was evaluated with regard to empirical data on human re-interpretation performance.Our work contributes an integrated theory for selective attention and a simulation-based investigation of its role in mental image reinterpretation. We have developed and evaluated a method for investigating the causal structure of cognitive models using interactive activation modeling and systematic computer simulations. Also, we account for our experience in combining computer science methods with the cognitive modeling paradigm.