A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

ANIMATED TRANSITION IN SIMILARITY-BASED TILED IMAGE LAYOUT

Effective techniques for organizing and visualizing large image collections are in growing demand as visual search gets increasingly popular. iMap is a treemap representation for visualizing and navigating image search and clustering results based on the evaluation of image similarity using both visual and textual information. iMap not only makes effective use of available display area to arrange images but also maintains stable update when images are inserted or removed during the query. A key challenge of using iMap lies in the difficult to follow and track the changes when updating the image arrangement as the query image changes. For many information visualization applications, showing the transition when interacting with the data is critically important as it can help users better perceive the changes and understand the underlying data. This work investigates the effectiveness of animated transition in a tiled image layout where the spiral arrangement of the images is based on their similarity. Three aspects of animated transition are considered, including animation steps, animation actions, and flying paths. Exploring and weighting the advantages and disadvantages of different methods for each aspect and in conjunction with the characteristics of the spiral image layout, we present an integrated solution, called AniMap, for animating the transition from an old layout to a new layout when a different image is selected as the query image. To smooth the animation and reduce the overlap among images during the transition, we explore different factors that might have an impact on the animation and propose our solution accordingly. We show the effectiveness of our animated transition solution by demonstrating experimental results and conducting a comparative user study.