Advanced Hybrid Simulation Model Based on Phenomenology and Artificial Intelligence


Book Description

Hybrid simulation technology is being widely used in the field of structural engineering for testing of structural systems to study their dynamic behavior under seismic loads. It involves coupling of experimental laboratory testing of complex parts of a system with computational models of the remaining parts of the system whose behavior can be simulated with confidence in a finite element program. A hybrid engine program helps the experimental and computational modules to interact with each other in real-time under seismic loading, and gives the overall response of the entire system as a whole. However, to conduct hybrid testing of even the simplest of systems, the number of experimental tests required exceed the capabilities of any laboratory in the country. All research in this field to date has been conducted either using highly simplified models, or by compromising the accuracy of the overall results by performing experimental testing of only a few most complex sub-structures of the structural system. The current project delivers an advanced hybrid simulation (AHS) model that removes the current limitations of hybrid simulation technology. It engages a single experimental module per type of sub-structure that is complex enough to require experimental testing, and predicts the hysteretic response of all similar sub-structures present in the entire structural system using phenomenology and artificial intelligence. This, coupled with the response of computational models of rest of the system at every increment, provides highly realistic and economical results by drastically cutting down the number of experimental tests required for hybrid testing. The present work removes the limitations of the existing phenomenological models and employs them to make the predictions. The AHS model is independent of material and geometry of the sub-structure, as it just requires inputs from the experimental response of a sub-structure at every load increment to predict the response of all similar sub-structures to any type of loading.







Consciousness in Humanoid Robots


Book Description

Building a conscious robot is a scientific and technological challenge. Debates about the possibility of conscious robots and the related positive outcomes and hazards for human beings are today no longer confined to philosophical circles. Robot consciousness is a research field aimed at a two-part goal: on the one hand, scholars working in robot consciousness take inspiration from biological consciousness to build robots that present forms of experiential and functional consciousness. On the other hand, scholars employ robots as tools to better understand biological consciousness. Thus, part one of the goal concerns the replication of aspects of biological consciousness in robots, by unifying a variety of approaches from AI and robotics, cognitive robotics, epigenetic and affective robotics, situated and embodied robotics, developmental robotics, anticipatory systems, and biomimetic robotics. Part two of the goal is pursued by employing robots to advance and mark progress in the study of consciousness in humans and animals. Notably, neuroscientists involved in the study of consciousness do not exclude the possibility that robots may be conscious. This eBook comprises a collection of thirteen manuscripts and an Editorial published by Frontiers in Robotics and Artificial Intelligence, under the section Humanoid Robotics, and Frontiers in Neurorobotics, on the topic “Consciousness in Humanoid Robots.” This compendium aims at collating the most recent theoretical studies, models, and case studies of machine consciousness that take the humanoid robot as a frame of reference. The content in the articles may be applied to many different kinds of robots, and to software agents as well.







Phenomenology of Perception


Book Description

Buddhist philosophy of Anicca (impermanence), Dukkha (suffering), and




Phantasmal Media


Book Description

An argument that great expressive power of computational media arises from the construction of phantasms—blends of cultural ideas and sensory imagination. In Phantasmal Media, D. Fox Harrell considers the expressive power of computational media. He argues, forcefully and persuasively, that the great expressive potential of computational media comes from the ability to construct and reveal phantasms—blends of cultural ideas and sensory imagination. These ubiquitous and often-unseen phantasms—cognitive phenomena that include sense of self, metaphors, social categories, narrative, and poetic thinking—influence almost all our everyday experiences. Harrell offers an approach for understanding and designing computational systems that have the power to evoke these phantasms, paying special attention to the exposure of oppressive phantasms and the creation of empowering ones. He argues for the importance of cultural content, diverse worldviews, and social values in computing. The expressive power of phantasms is not purely aesthetic, he contends; phantasmal media can express and construct the types of meaning central to the human condition. Harrell discusses, among other topics, the phantasm as an orienting perspective for developers; expressive epistemologies, or data structures based on subjective human worldviews; morphic semiotics (building on the computer scientist Joseph Goguen's theory of algebraic semiotics); cultural phantasms that influence consensus and reveal other perspectives; computing systems based on cultural models; interaction and expression; and the ways that real-world information is mapped onto, and instantiated by, computational data structures. The concept of phantasmal media, Harrell argues, offers new possibilities for using the computer to understand and improve the human condition through the human capacity to imagine.




Agent-based Modeling and Simulation in Archaeology


Book Description

Archaeology has been historically reluctant to embrace the subject of agent-based simulation, since it was seen as being used to "re-enact" and "visualize" possible scenarios for a wider (generally non-scientific) audience, based on scarce and fuzzy data. Furthermore, modeling "in exact terms" and programming as a means for producing agent-based simulations were simply beyond the field of the social sciences. This situation has changed quite drastically with the advent of the internet age: Data, it seems, is now ubiquitous. Researchers have switched from simply collecting data to filtering, selecting and deriving insights in a cybernetic manner. Agent-based simulation is one of the tools used to glean information from highly complex excavation sites according to formalized models, capturing essential properties in a highly abstract and yet spatial manner. As such, the goal of this book is to present an overview of techniques used and work conducted in that field, drawing on the experience of practitioners.




Artificial Intelligence


Book Description

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI. In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.




Simulation and Learning


Book Description

The main idea of this book is that to comprehend the instructional potential of simulation and to design effective simulation-based learning environments, one has to consider both what happens inside the computer and inside the students' minds. The framework adopted to do this is model-centered learning, in which simulation is seen as particularly effective when learning requires a restructuring of the individual mental models of the students, as in conceptual change. Mental models are by themeselves simulations, and thus simulation models can extend our biological capacity to carry out simulative reasoning. For this reason, recent approaches in cognitive science like embodied cognition and the extended mind hypothesis are also considered in the book.. A conceptual model called the “epistemic simulation cycle” is proposed as a blueprint for the comprehension of the cognitive activies involved in simulation-based learning and for instructional design.




NASA SP.


Book Description