Indirect sensing through abstractive learning.

The paper discusses disparity issues in sensing tasks involving the production of a 'high-level' signal from 'low-level' signal sources. It introduces an abstraction theory which helps to explain the nature of the problem and point the way to a solution. It proposes a solution based on the use of supervised adaptive methods drawn from artificial intelligence. Finally, it describes a set of empirical experiments which were carried out to evaluate the efficacy of the method

Space exploration: The interstellar goal and Titan demonstration

Automated interstellar space exploration is reviewed. The Titan demonstration mission is discussed. Remote sensing and automated modeling are considered. Nuclear electric propulsion, main orbiting spacecraft, lander/rover, subsatellites, atmospheric probes, powered air vehicles, and a surface science network comprise mission component concepts. Machine, intelligence in space exploration is discussed

ConceptEVA: Concept-Based Interactive Exploration and Customization of Document Summaries

With the most advanced natural language processing and artificial intelligence approaches, effective summarization of long and multi-topic documents -- such as academic papers -- for readers from different domains still remains a challenge. To address this, we introduce ConceptEVA, a mixed-initiative approach to generate, evaluate, and customize summaries for long and multi-topic documents. ConceptEVA incorporates a custom multi-task longformer encoder decoder to summarize longer documents. Interactive visualizations of document concepts as a network reflecting both semantic relatedness and co-occurrence help users focus on concepts of interest. The user can select these concepts and automatically update the summary to emphasize them. We present two iterations of ConceptEVA evaluated through an expert review and a within-subjects study. We find that participants' satisfaction with customized summaries through ConceptEVA is higher than their own manually-generated summary, while incorporating critique into the summaries proved challenging. Based on our findings, we make recommendations for designing summarization systems incorporating mixed-initiative interactions.Comment: 16 pages, 7 figure

Liberating from literalness : making space for meaningful forms of abstraction

There is a need for some alternative approaches to the way that undergraduate teacher education programs have traditionally been delivered. Our warrant for this assertion is derived, in the first instance, from the work of Aronowitz and Giroux who have argued that there are many different signs of a crisis of cognition within all levels of education. Twenty years later the conditions that they described seem even more entrenched. This paper argues for a fresh inquiry into the deeper logics of learning and teaching, by drawing primarily on the work of James, Dewey, Kierkegaard, Britzman and Mackay. There is also a brief inclusion of anecdotes from some initial applications of these theories into our own practice

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

Conversational Agent: Developing a Model for Intelligent Agents with Transient Emotional States

The inclusion of human characteristics (i.e., emotions, personality) within an intelligent agent can often increase the effectiveness of information delivery and retrieval. Chat-bots offer a plethora of benefits within an eclectic range of disciplines (e.g., education, medicine, clinical and mental health). Hence, chatbots offer an effective way to observe, assess, and evaluate human communication patterns. Current research aims to develop a computational model for conversational agents with an emotional component to be applied to the army leadership training program that will allow for the examination of interpersonal skills in future research. Overall, the current research explores the application of the deep learning algorithm to the development of a generalized framework that will be based upon modeling empathetic conversation between an intelligent conversational agent (chatbot) and a human user in order to allow for higher level observation of interpersonal communication skills. Preliminary results demonstrate the promising potential of the seq2seq technique (e.g., through the use of Dialog Flow Chatbot platform) when applied to emotion-oriented conversational tasks. Both the classification and generative conversational modeling tasks demonstrate the promising potential of the current research for representing human to agent dialogue. However, this implementation may be extended by utilizing, a larger more high-quality dataset

A study of the modes of imagination

Though this study had its origins in the consideration of children's writing and their responses to reading it explores in a wider context the nature of imagination and its relation to the discursive. Within imagination there seem to be three modes that are frequently conflated - fantasy, identification and the imagination itself. Each, however, has distinctive epistemological implications and significance for identity. In normal discourse imagination is often conflated with fantasy. Whereas fantasy seeks to exercise power in attempting to transform the world into its own terms and imagination shares this capacity for refiguration, the one is associated with obfuscation and the other with insight. In reading, the distinction is crucial. Generally, children are empowered by the fantasy that texts exploit or stimulate. Yet the absence of significant cognitive control constitutes a kind of blindness. Identification differs from fantasy in that the reader is drawn, say, into the world of the book - this supposes a differentiation, an escape, from the self that is merely placated in fantasy. Yet, here too, is blindness, particularly with regard to the constitutive aspects of the writing. On the other hand to teach texts through exerting cognitive control may shift the text too quickly into the discursive with the danger that students are expected to respond to experiences that they have not had. The distinctions between identification and imagination are manifest in some of the fictions of Chaucer and Kafka where differentiation is achieved through irony. Imagination is what facilitates the s

Developing Error Handling Software for Object-Oriented Geographical Information

The inclusion of error handling capabilities within geographical information systems (GIS) is seen by many as crucial to the future commercial and legal stability of the technology. This thesis describes the analysis, design, implementation and use of a GIS able to handle both geographical information (GI) and the error associated with that GI. The first stage of this process is the development of an error-sensitive GIS, able to provide core error handling functionality in a form flexible enough to be widely applicable to error-prone GI. Object-oriented (OO) analysis, design and programming techniques, supported by recent developments in formal OO theory, are used to implement an error-sensitive GIS within Laser-Scan Gothic OOGIS software. The combination of formal theory and GIS software implementation suggests that error-sensitive GIS are a practical possibility using OO technology. While the error-sensitive GIS is an important step toward full error handling systems, it is expected that most GIS users would require additional high level functionality before use of error- sensitive GIS could become commonplace. There is a clear need to provide error handling systems that actively assist non-expert users in assessing, using and understanding error in GI. To address this need, an error-aware GIS offering intelligent domain specific error handling software tools was developed, based on the core error-sensitive functionality. In order to provide a stable software bridge between the flexible error-sensitive GIS and specialised error-aware software tools, the error-aware GIS makes use of a distributed systems component architecture. The component architecture allows error-aware software tools that extend core error-sensitive functionality to be developed with minimal time and cost overheads. Based on a telecommunications application in Kingston-upon-Hull, UK, three error-aware tools were developed to address particular needs identified within the application. First, an intelligent hypertext system in combination with a conventional expert system was used to assist GIS users with error-sensitive database design. Second, an inductive learning algorithm was used to automatically populate the error-sensitive database with information about error, based on a small pilot error assessment. Finally, a visualisation and data integration tool was developed to allow access to the error-sensitive database and error propagation routines to users across the Internet. While a number of important avenues of further work are implied by this research, the results of this research provide a blueprint for the development of practical error handling capabilities within GIS. The architecture used is both robust and flexible, and arguably represents a framework both for future research and for the development of commercial error handling GIS

The Neuropsychology of Religion

Consider religion to be a community's (1) costly and hard-to-fake commitment (2) to a counterfactual world of supernatural agents (3) who master people's existential anxieties, such as death and deception. This intellectual framework guides a research program that aims to foster scientific dialogue between cultural anthropology, cognitive psychology and evolutionary biology regarding a set of phenomena vital to most human life and all societies (Atran 2002). The present chapter mainly concerns the third criterion of religion (3), and its implications for neuropsychology. Previous neurobiological studies of religion have focused on tracking participant's neurophysiological responses during episodes of religious experience and recording individual patterns of trance, vision, revelation and the like. This has favored comparison of religious experience with temporal-lobe brain-wave patterns during epileptic seizures and acute schizophrenic episodes. Cognitive structures of the human mind/brain in general, and cognitions of agency in particular, are usually represented in these studies in simple-minded terms (e.g., binary oppositions, holistic vs. analytical tensions, hierarchical organization, etc.) that have little input from, or pertinence to, recent findings of cognitive and developmental psychology. Perhaps more telling is recent work on the role of the prefrontal cortices in processing concepts of agency and self and in cognitive mediation of relevant emotions originating in (what was once called) “the limbic system.” Still, for those religious believers who never have an emotionally intense encounter with the Divine – including the overwhelming majority of persons in our society – the neurophysiological bases of faith remain a complete mystery