In traditional tasks of formal reasoning, participants are asked to evaluate the validity of logical arguments. While this research tradition has contributed in many ways to our understanding of human reasoning, the extent to which this body of research generalizes to everyday, or informal, reasoning is unclear (e.g., Evans & Thompson, 2004; Galotti, 1989). The main goal of this dissertation was to illustrate the benefits of applying an informal approach to the study of conditional reasoning. In six experiments, everyday conditionals in the form of inducements (promises and threats) and advice (tips and warnings) were investigated. The results support three main conclusions. First, people recruit a substantial amount of background knowledge when interpreting and reasoning with these conditionals. Specifically, inducements were found to be different from advice on several pragmatic variables (Experiment 1); these variables also predicted differences in inference patterns (Experiment 2). Second, these studies provide further support for a probabilistic interpretation of conditionals (e.g., Evans & Over, 2004; Oaksford & Chater, 2001). Thus, in Experiments 3-5, estimates of different conditional probabilities predicted a number of judgments people make about inducements and advice. A particularly interesting finding was that the effectiveness of these conditionals in changing behaviour did not seem to depend on how likely they were perceived to be true. Finally, Experiment 6 adopted a decision-theoretic analysis (e.g., Over, Manktelow, & Hadjichristidis, 2004), showing that the effectiveness and quality of inducements and advice were tied to perceptions of subjective utility and preferences among possible outcomes. This dissertation concludes with a theoretical discussion of the nature of the relationship between formal and informal reasoning.

The present research involved two studies that considered ecology-centered experiences (i.e., experiences with living things) as a factor in children’s environmental attitudes and behaviors and adolescents’ ecological understanding. The first study (Study 1) examined how a community garden provides children in an urban setting the opportunity to learn about ecology through ecology-centered experiences. To do this, I carried out a yearlong ethnographic study at an urban community garden located in a large city in the Southeastern United States. Through participant observations and informal interviews of community garden staff and participants, I found children had opportunities to learn about ecology through ecology-centered experiences (e.g., interaction with animals) along with other experiences (e.g., playing games, reading books). In light of previous research that shows urban children have diminished ecological thought—a pattern of thought that privileges the relationship between living things—because of their lack of ecology-centered experiences (Coley, 2012), the present study may have implications for urban children to learn about ecology. As an extension of Study 1, I carried out a second study (Study 2) to investigate how ecology-centered experiences contribute to adolescents’ environmental attitudes and behaviors in light of other contextual factors, namely environmental responsibility support, ecological thought, age and gender. Study 2 addressed three research questions. First, does ecological thought—a pattern of thought that privileges the relationship between living things—predict environmental attitudes and behaviors (EAB)? Results showed ecological thought did not predict EAB, an important finding considering the latent assumptions of previous research about the relationship between these two factors (e.g., Brugger, Kaiser, & Roczen, 2011). Second, do two types of contextual support, ecology-centered experiences (i.e., experiences with living things) and environmental responsibility support (i.e., support through the availability of environmentally responsible models) predict EAB? As predicted, results showed that ecology-centered experiences predicted EAB; yet, when environmental responsibility support was taken into consideration, ecology-centered experiences no longer predicted EAB. These findings suggested environmental responsibility support was a stronger predictor than ecology-centered experiences. Finally, do age and gender predict EAB? Consistent with previous research (e.g., Alp, Ertepiner, Tekkaya, & Yilmaz, 2006), age and gender significantly predicted EAB.

Fusion of information from multiple modalities in Human Computer Interfaces (HCI) has gained a lot of attention in recent years, and has far reaching implications in many areas of human-machine interaction. However, a major limitation of current HCI fusion systems is that the fusion process tends to ignore the semantic nature of modalities, which may reinforce, complement or contradict each other over time. Also, most systems are not robust in representing the ambiguity inherent in human gestures. In this work, we investigate an evidential reasoning based approach for intelligent multimodal fusion, and apply this algorithm to a proposed multimodal system consisting of a Hand Gesture sensor and a Brain Computing Interface (BCI). There are three major contributions of this work to the area of human computer interaction. First, we propose an algorithm for reconstruction of the 3D hand pose given a 2D input video. Second, we develop a BCI using Steady State Visually Evoked Potentials, and show how a multimodal system consisting of the two sensors can improve the efficiency and the complexity of the system, while retaining the same levels of accuracy. Finally, we propose an semantic fusion algorithm based on Transferable Belief Models, which can successfully fuse information from these two sensors, to form meaningful concepts and resolve ambiguity. We also analyze this system for robustness under various operating scenarios.

As a technique to solve new problems based on previous successful cases, CBR represents significant prospects for improving the accuracy and effectiveness of unstructured decision-making problems. Similar problems have similar solutions is the main assumption. Utility oriented similarity modeling is gradually becoming an important direction for Case-based reasoning research. In this thesis, we propose a new way to represent the utility of case by using fuzzy rules. Our method could be considered as a new way to estimate case utility based on fuzzy rule based reasoning. We use modified WANG’s algorithm to generate a fuzzy if-then rule from a case pair instead of a single case. The fuzzy if-then rules have been identified as a powerful means to capture domain information for case utility approximation than traditional similarity measures based on feature weighting. The reason why we choose the WANG algorithm as the foundation is that it is a simpler and faster algorithm to generate if-then rules from examples. The generated fuzzy rules are utilized as a case matching mechanism to estimate the utility of the cases for a given problem. The given problem will be formed with each case in the case library into pairs which are treated as the inputs of fuzzy rules to determine whether or to which extent a known case is useful to the problem. One case has an estimated utility score to the given problem to help our system to make decision. The experiments on several data sets have showed the superiority of our method over traditional schemes, as well as the feasibility of learning fuzzy if-then rules from a small number of cases while still having good performances.

Three experiments were conducted to investigate the hypothesis that young infants? failures to search for occluded objects arises, not from deficiencies in their object representations, but from limitations in experience with the physical world. Successful means-end search is typically found at 8 months of age and is traditionally taken as the hallmark of object permanence. However, recent evidence suggests that infants much younger than 8 months of age are able to represent and reason about objects that are no longer visible. In Experiment 1, successful means-end search was found for 8. 5-, but not 6. 5-month-old infants in a traditional task, but younger infants showed successful search ability when the task was made familiar to them in Experiment 2 (i. e. , when the toy and occluder are first presented as a single composite object), and when they were given the opportunity to watch a demonstration of the solution to the task in Experiment 3. These results are taken as evidence for the ?experiential limitation? hypothesis and suggest that young infants are more apt at solving manual search tasks than previously acknowledged.

Fusion of information from multiple modalities in Human Computer Interfaces (HCI) has gained a lot of attention in recent years, and has far reaching implications in many areas of human-machine interaction. However, a major limitation of current HCI fusion systems is that the fusion process tends to ignore the semantic nature of modalities, which may reinforce, complement or contradict each other over time. Also, most systems are not robust in representing the ambiguity inherent in human gestures. In this work, we investigate an evidential reasoning based approach for intelligent multimodal fusion, and apply this algorithm to a proposed multimodal system consisting of a Hand Gesture sensor and a Brain Computing Interface (BCI). There are three major contributions of this work to the area of human computer interaction. First, we propose an algorithm for reconstruction of the 3D hand pose given a 2D input video. Second, we develop a BCI using Steady State Visually Evoked Potentials, and show how a multimodal system consisting of the two sensors can improve the efficiency and the complexity of the system, while retaining the same levels of accuracy. Finally, we propose an semantic fusion algorithm based on Transferable Belief Models, which can successfully fuse information from these two sensors, to form meaningful concepts and resolve ambiguity. We also analyze this system for robustness under various operating scenarios.

In traditional tasks of formal reasoning, participants are asked to evaluate the validity of logical arguments. While this research tradition has contributed in many ways to our understanding of human reasoning, the extent to which this body of research generalizes to everyday, or informal, reasoning is unclear (e.g., Evans & Thompson, 2004; Galotti, 1989). The main goal of this dissertation was to illustrate the benefits of applying an informal approach to the study of conditional reasoning. In six experiments, everyday conditionals in the form of inducements (promises and threats) and advice (tips and warnings) were investigated. The results support three main conclusions. First, people recruit a substantial amount of background knowledge when interpreting and reasoning with these conditionals. Specifically, inducements were found to be different from advice on several pragmatic variables (Experiment 1); these variables also predicted differences in inference patterns (Experiment 2). Second, these studies provide further support for a probabilistic interpretation of conditionals (e.g., Evans & Over, 2004; Oaksford & Chater, 2001). Thus, in Experiments 3-5, estimates of different conditional probabilities predicted a number of judgments people make about inducements and advice. A particularly interesting finding was that the effectiveness of these conditionals in changing behaviour did not seem to depend on how likely they were perceived to be true. Finally, Experiment 6 adopted a decision-theoretic analysis (e.g., Over, Manktelow, & Hadjichristidis, 2004), showing that the effectiveness and quality of inducements and advice were tied to perceptions of subjective utility and preferences among possible outcomes. This dissertation concludes with a theoretical discussion of the nature of the relationship between formal and informal reasoning.

The procedure for developing a new product, in general, is as follows. First, the design engineer must have a thorough understanding regarding the encountered problem. And, he must produce some design concepts based on the perceived requirements. Finally, some solutions are then achieved according to the prescribed design concepts. Unfortunately, few researchers have been able to explain, in a specific rather than abstract manner, the process of generating pertinent design concepts. However, this process has to be a very critical link in the chain. Without obtaining a good design concept the entire design procedure will fall, not to mention to find a suitable solution. In this research we use an interesting analogy between the design procedure and the well-familiarized Sun/Water-cycle system, to concretely describe the task of inspiration of innovative concepts particularly in engineering design. The use of this analogy, we believe, will guide engineers to more effectively and more efficiently go through the stages of conceptual design. Consequently, the entire product development time can be reduced.

Thesis (Ph. D.)--University of Rochester, 1985. / "September 1985."

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 230-235). Available also in a digital version from Dissertation Abstracts.