Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Technology Directions for the 21st Century

The Office of Space Communications (OSC) is tasked by NASA to conduct a planning process to meet NASA's science mission and other communications and data processing requirements. A set of technology trend studies was undertaken by Science Applications International Corporation (SAIC) for OSC to identify quantitative data that can be used to predict performance of electronic equipment in the future to assist in the planning process. Only commercially available, off-the-shelf technology was included. For each technology area considered, the current state of the technology is discussed, future applications that could benefit from use of the technology are identified, and likely future developments of the technology are described. The impact of each technology area on NASA operations is presented together with a discussion of the feasibility and risk associated with its development. An approximate timeline is given for the next 15 to 25 years to indicate the anticipated evolution of capabilities within each of the technology areas considered. This volume contains four chapters: one each on technology trends for database systems, computer software, neural and fuzzy systems, and artificial intelligence. The principal study results are summarized at the beginning of each chapter

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

Building a Science of Animal Minds: Lloyd Morgan, Experimentation, and Morgan’s Canon

Conwy Lloyd Morgan (1852–1936) is widely regarded as the father of modern comparative psychology. Yet, Morgan initially had significant doubts about whether a genuine science of comparative psychology was even possible, only later becoming more optimistic about our ability to make reliable inferences about the mental capacities of non-human animals. There has been a fair amount of disagreement amongst scholars of Morgan’s work about the nature, timing, and causes of this shift in Morgan’s thinking. We argue that Morgan underwent two quite different shifts of attitude towards the proper practice of comparative psychology. The first was a qualified acceptance of the Romanesian approach to comparative psychology that he had initially criticized. The second was a shift away from Romanes’ reliance on systematizing anecdotal evidence of animal intelligence towards an experimental approach, focused on studying the development of behaviour. We emphasize the role of Morgan’s evolving epistemological views in bringing about the first shift – in particular, his philosophy of science. We emphasize the role of an intriguing but overlooked figure in the history of comparative psychology in explaining the second shift, T. Mann Jones, whose correspondence with Morgan provided an important catalyst for Morgan’s experimental turn, particularly the special focus on development. We also shed light on the intended function of Morgan’s Canon, the methodological principle for which Morgan is now mostly known. The Canon can only be properly understood by seeing it in the context of Morgan’s own unique experimental vision for comparative psychology

Artificial intelligence : a heuristic search for commercial and management science applications

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1984.MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.Bibliography: leaves 185-188.by Philip A. Cooper.M.S

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered

Modifiability Of Strategy Use In Probabilistic Categorization By Rhesus Macaques (Macaca Mulatta) And Capuchin Monkeys (Cebus [Sapajus] Apella)

Humans and nonhuman animals categorize the natural world, and their behaviors can reveal how they use the stimulus information they encounter in service of these categorizations. Rigorous psychological study of categorization has offered many insights into the processes of categorization and their relative strengths and weaknesses across species. Probabilistic categorization, in which the relationships among stimulus information and category membership that are observed by an individual are fundamentally probabilistic, presents unique challenges both to the categorizer and to the psychologist attempting to model their behavior. Challenges notwithstanding, probabilistic categorization is an exceptionally ecologically relevant problem to human and nonhuman animal cognition alike. This dissertation reports the effects of many manipulations of theoretical interest on computer-trained rhesus macaques’ and capuchin monkeys’ inferred cognitive strategy use in a computerized version of a classic probabilistic categorization task. Experiment 1 probed cognitive strategy use across five variants of the same task in which the probability structure was constant, but the appearances and onscreen locations of cues and responses changed. Experiment 2 presented a series of manipulations of theoretical interest to the animals by changing the probability and reward structures of the task. Experiment 3 manipulated the stimuli of the task in ways motivated by findings across perceptual psychology literature. Experiment 4 extended the reward rate manipulations of Experiment 2 even further. Across four experiments, inferred strategy use was remarkably stable. Those animals that used cue-based strategies often returned to the same specific strategy experiment after experiment, as the cues, responses, probabilities, and contingencies changed around them. This finding is discussed in relation to questions of a real or functional ceiling on sophistication of strategy use, the robustness of cognitive individual differences in nonhuman primates, and future directions for comparative study of cognitive strategy use in probabilistic categorization