ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning  (12)
  • climate change
  • risk assessment
  • The MIT Press  (18)
Collection
Keywords
Publisher
Language
Years
  • 1
    facet.materialart.
    Unknown
    Educating for the Anthropocene (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2022-11-18
    Description: The work of environmental educators and activists in India and South Africa offers new models for schooling and environmental activism. Education has never played as critical a role in determining humanity's future as it does in the Anthropocene, an era marked by humankind's unprecedented control over the natural environment. Drawing on a multisited ethnographic project among schools and activist groups in India and South Africa, Peter Sutoris explores education practices in the context of impoverished, marginal communities where environmental crises intersect with colonial and racist histories and unsustainable practices. He exposes the depoliticizing effects of schooling and examines cross-generational knowledge transfer within and beyond formal education. Finally, he calls for the bridging of schooling and environmental activism, to find answers to the global environmental crisis. The onset of the Anthropocene challenges the very definition of education and its fundamental goals, says Sutoris. Researchers must look outside conventional models and practices of education for inspiration if education is to live up to its responsibilities at this critical time. For decades, environmental activist movements in some countries have wrestled with questions of responsibility and action in the face of environmental destruction; they inhabited the mental world of the Anthropocene before much of the rest of the world. Sutoris highlights an innovative research methodology of participatory observational filmmaking, describing how films made by children in the Indian and South African communities provide a window into the ways that young people make sense of the future of the Anthropocene. It is through their capacity to imagine the world differently, Sutoris argues, that education can reinvent itself.
    Keywords: Environmental education ; education for sustainable development ; the Anthropocene ; environmental crisis ; climate change ; India ; South Africa ; activism ; visual ethnography ; observational film ; Uttarakhand ; Tehri Dam ; South Durban ; bic Book Industry Communication::J Society & social sciences::JN Education::JNA Philosophy & theory of education ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RND Environmental policy & protocols
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 2
    facet.materialart.
    Unknown
    Boosting (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
    Keywords: Artificial intelligence ; Algorithms and data structures ; thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 3
    facet.materialart.
    Unknown
    Artificial Life IX (2022)
    The MIT Press | A Bradford Book
    Details
    Publication Date: 2024-04-11
    Description: Proceedings from the ninth International Conference on Artificial Life; papers by scientists of many disciplines focusing on the principles of organization and applications of complex, life-like systems. Artificial Life is an interdisciplinary effort to investigate the fundamental properties of living systems through the simulation and synthesis of life-like processes. The young field brings a powerful set of tools to the study of how high-level behavior can arise in systems governed by simple rules of interaction. Some of the fundamental questions include: What are the principles of evolution, learning, and growth that can be understood well enough to simulate as an information process? Can robots be built faster and more cheaply by mimicking biology than by the product design process used for automobiles and airplanes? How can we unify theories from dynamical systems, game theory, evolution, computing, geophysics, and cognition? The field has contributed fundamentally to our understanding of life itself through computer models, and has led to novel solutions to complex real-world problems across high technology and human society. This elite biennial meeting has grown from a small workshop in Santa Fe to a major international conference. This ninth volume of the proceedings of the international A-life conference reflects the growing quality and impact of this interdisciplinary scientific community.
    Keywords: Artificial intelligence ; Robotics ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 4
    facet.materialart.
    Unknown
    Linguistics for the Age of AI (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning—the deep, context-sensitive meaning that a person derives from spoken or written language. With Linguistics for the Age of AI, McShane and Nirenburg offer a roadmap for creating language-endowed intelligent agents (LEIAs) that can understand,explain, and learn. They describe the language-understanding capabilities of LEIAs from the perspectives of cognitive modeling and system building, emphasizing “actionability”—which involves achieving interpretations that are sufficiently deep, precise, and confident to support reasoning about action. After detailing their microtheories for topics such as semantic analysis, basic coreference, and situational reasoning, McShane and Nirenburg turn to agent applications developed using those microtheories and evaluations of a LEIA's language understanding capabilities. McShane and Nirenburg argue that the only way to achieve human-level language understanding by machines is to place linguistics front and center, using statistics and big data as contributing resources. They lay out a long-term research program that addresses linguistics and real-world reasoning together, within a comprehensive cognitive architecture.
    Keywords: natural language understanding ; computational semantics ; computational pragmatics ; computational linguistics ; intelligent agents ; cognitive modelling ; cognitive systems ; AI ; artificial intelligence ; language-endowed intelligent agents ; natural language processing ; NLP ; language-endowed intelligent agent systems ; linguistic and extralinguistic scope ; understanding ; Extracting and representing meaning ; theories ; systems and models ; actionability ; explanation ; Theory and methodology ; knowledge bases ; incrementality ; microtheories ; Pre-semantic analysis ; error recovery ; managing complexity ; Modification ; proposition-level semantic enhancements ; constructions ; indirect speech acts ; non-literal language ; ellipsis ; fragments ; unknown words ; personal pronouns ; broad referring expressions ; definite descriptions ; anaphoric event coreference ; Residual ambiguities ; incongruities ; underspecification ; incorporating ; OntoAgent cognitive architecture ; fractured syntax ; treating underspecified elements ; Integrated NLU applications ; Maryland Virtual Patient ; cognitive robotics ; Model and system evaluation ; component-level evaluation ; holistic evaluation ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::C Language and Linguistics::CF Linguistics::CFM Lexicography ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GT Interdisciplinary studies::GTK Cognitive studies
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 5
    facet.materialart.
    Unknown
    Global Meat (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2022-02-21
    Description: The growth of the global meat industry and the implications for climate change, food insecurity, workers' rights, the treatment of animals, and other issues. Global meat production and consumption have risen sharply and steadily over the past five decades, with per capita meat consumption almost doubling since 1960. The expanding global meat industry, meanwhile, driven by new trade policies and fueled by government subsidies, is dominated by just a few corporate giants. Industrial farming—the intensive production of animals and fish—has spread across the globe. Millions of acres of land are now used for pastures, feed crops, and animal waste reservoirs. Drawing on concrete examples, the contributors to Global Meat explore the implications of the rise of a global meat industry for a range of social and environmental issues, including climate change, clean water supplies, hunger, workers' rights, and the treatment of animals. Three themes emerge from their discussions: the role of government and corporations in shaping the structure of the global meat industry; the paradox of simultaneous rising meat production and greater food insecurity; and the industry's contribution to social and environmental injustice. Contributors address such specific topics as the dramatic increase in pork production and consumption in China; land management by small-scale cattle farmers in the Amazon; the effect on the climate of rising greenhouse gas emissions from cattle raised for meat; and the tensions between economic development and animal welfare. Contributors Conner Bailey, Robert M. Chiles, Celize Christy, Riva C. H. Denny, Carrie Freshour, Philip H. Howard, Elizabeth Ransom, Tom Rudel, Mindi Schneider, Nhuong Tran, Bill Winders
    Keywords: Globalization ; meat industry ; aquaculture ; corporations ; poultry ; pork ; chicken ; beef ; fish ; CAFOs ; animal welfare ; environment ; labor ; China ; Rwanda ; Ecuador ; United States ; climate change ; solutions ; consumption ; meat processing ; subsidies ; agricultural subsidies ; seafood ; fisheries ; livestock ; industrial livestock ; agribusiness ; immigration ; race ; deportation ; USDA ; emissions ; nutrition ; animal rights ; nutrition transition ; dietary transition ; sustainability ; sustainable development ; vegetarianism ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RND Environmental policy & protocols ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNP Pollution & threats to the environment
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 6
    facet.materialart.
    Unknown
    Catastrophes, Confrontations, and Constraints (2023)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2023-07-31
    Description: A ground-breaking study on how natural disasters can escalate or defuse wars, insurgencies, and other strife.Armed conflict and natural disasters have plagued the twenty-first century. Not since the end of World War II has the number of armed conflicts been higher. At the same time, natural disasters have increased in frequency and intensity over the past two decades, their impacts worsened by climate change, urbanization, and persistent social and economic inequalities. Providing the first comprehensive analysis of the interplay between natural disasters and armed conflict, Catastrophes, Confrontations, and Constraints explores the extent to which disasters facilitate the escalation or abatement of armed conflicts—as well as the ways and contexts in which combatants exploit these catastrophes. Tobias Ide utilizes both qualitative insights and quantitative data to explain the link between disasters and the (de-)escalation of armed conflict and presents over thirty case studies of earthquakes, droughts, floods, and storms in Africa, the Middle East, Asia, and Latin America. He also examines the impact of COVID-19 on armed conflicts in Iraq, Afghanistan, Nigeria, and the Philippines. Catastrophes, Confrontations, and Constraints is an invaluable addition to current debates on climate change, environmental stress, and security. Professionals and students will greatly appreciate the wealth of timely data it provides for their own investigations.
    Keywords: armed conflict ; civil war ; climate change ; disaster ; environment ; hazard ; insurgent ; rebel ; security ; violence ; aid ; cyclone ; drought ; earthquake ; flood ; government ; heat wave ; international relations ; opportunity ; politics ; storm ; tsunami ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RND Environmental policy & protocols ; bic Book Industry Communication::J Society & social sciences::JP Politics & government::JPS International relations::JPSN International institutions::JPSN2 EU & European institutions ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNR Natural disasters
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 7
    facet.materialart.
    Unknown
    Artificial Life VII (2022)
    The MIT Press | A Bradford Book
    Details
    Publication Date: 2024-04-14
    Description: The term "artificial life" describes research into synthetic systems that possess some of the essential properties of life. This interdisciplinary field includes biologists, computer scientists, physicists, chemists, geneticists, and others. Artificial life may be viewed as an attempt to understand high-level behavior from low-level rules—for example, how the simple interactions between ants and their environment lead to complex trail-following behavior. An understanding of such relationships in particular systems can suggest novel solutions to complex real-world problems such as disease prevention, stock-market prediction, and data mining on the Internet. Since their inception in 1987, the Artificial Life meetings have grown from small workshops to truly international conferences, reflecting the field's increasing appeal to researchers in all areas of science.
    Keywords: Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 8
    facet.materialart.
    Unknown
    Global Carbon Pricing (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2022-02-21
    Description: Why the traditional “pledge and review” climate agreements have failed, and how carbon pricing, based on trust and reciprocity, could succeed. After twenty-five years of failure, climate negotiations continue to use a “pledge and review” approach: countries pledge (almost anything), subject to (unenforced) review. This approach ignores everything we know about human cooperation. In this book, leading economists describe an alternate model for climate agreements, drawing on the work of the late Nobel laureate Elinor Ostrom and others. They show that a “common commitment” scheme is more effective than an “individual commitment” scheme; the latter depends on altruism while the former involves reciprocity (“we will if you will”). The contributors propose that global carbon pricing is the best candidate for a reciprocal common commitment in climate negotiations. Each country would commit to placing charges on carbon emissions sufficient to match an agreed global price formula. The contributors show that carbon pricing would facilitate negotiations and enforcement, improve efficiency and flexibility, and make other climate policies more effective. Additionally, they analyze the failings of the 2015 Paris climate conference. Contributors Richard N. Cooper, Peter Cramton, Ottmar Edenhofer, Christian Gollier, Éloi Laurent, David JC MacKay, William Nordhaus, Axel Ockenfels, Joseph E. Stiglitz, Steven Stoft, Jean Tirole, Martin L. Weitzman
    Keywords: emissions ; clean air ; climate change ; environmental economics ; CO2 ; greenhouse gases ; Paris Agreement ; free rider problem ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 9
    facet.materialart.
    Unknown
    Machine Learning for Data Streams (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.
    Keywords: data mining ; stream ; data ; mining ; statistics ; techniques ; analysis ; learning ; extract ; algorithm ; data stream ; MOA ; massive online analysis ; software ; implementation ; applications ; approximation ; big data ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 10
    facet.materialart.
    Unknown
    Reason and Less (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-05
    Description: A new, biologically driven model of human behavior in which reason is tethered to the evolutionarily older autonomic, instinctive, and associative systems. In Reason and Less, Vinod Goel explains the workings of the tethered mind. Reason does not float on top of our biology but is tethered to evolutionarily older autonomic, instinctive, and associative systems. After describing the conceptual and neuroanatomical basis of each system, Goel shows how they interact to generate a blended response. Goel's commonsense account drives human behavior back into the biology, where it belongs, and provides a richer set of tools for understanding how we pursue food, sex, and politics. Goel takes the reader on a journey through psychology (cognitive, behavioral, developmental, and evolutionary), neuroscience, philosophy, ethology, economics, and political science to explain the workings of the tethered mind. One key insight that holds everything together is that feelings—generated in old, widely conserved brain stem structures—are evolution's solution to initiating and selecting all behaviors, and provide the common currency for the different systems to interact. Reason is as much about feelings as are lust and the taste of chocolate cake. All systems contribute to behavior and the overall control structure is one that maximizes pleasure and minimizes displeasure. Tethered rationality has some sobering and challenging implications for such real-world human behaviors as climate change denial, Trumpism, racism, or sexism. They cannot be changed simply by targeting beliefs but will require more drastic measures, the nature of which depends on the specific behavior in question. Having an accurate model of human behavior is the crucial first step.
    Keywords: rational ; reasoning ; decision making ; instincts ; heuristics ; emotions ; feelings ; human nature ; irrational ; arational ; belief revision ; behavioral economics ; neural plasticity ; changing worldviews ; science denial ; human behavior ; human behaviour ; tethered rationality ; blended response ; brains ; neural development ; evolution ; minds ; politics ; conspiracy theories ; weight management ; climate change ; overeating ; lust ; sex ; food ; in group outgroup bias ; cheaters ; gender roles ; impeachment ; covid-19 ; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences ; thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCK Behavioural economics
    Language: English
    Format: application/octet-stream
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 11
    facet.materialart.
    Unknown
    Distributional Reinforcement Learning (2023)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-04
    Description: The first comprehensive guide to distributional reinforcement learning, providing a new mathematical formalism for thinking about decisions from a probabilistic perspective.Distributional reinforcement learning is a new mathematical formalism for thinking about decisions. Going beyond the common approach to reinforcement learning and expected values, it focuses on the total reward or return obtained as a consequence of an agent's choices—specifically, how this return behaves from a probabilistic perspective. In this first comprehensive guide to distributional reinforcement learning, Marc G. Bellemare, Will Dabney, and Mark Rowland, who spearheaded development of the field, present its key concepts and review some of its many applications. They demonstrate its power to account for many complex, interesting phenomena that arise from interactions with one's environment.The authors present core ideas from classical reinforcement learning to contextualize distributional topics and include mathematical proofs pertaining to major results discussed in the text. They guide the reader through a series of algorithmic and mathematical developments that, in turn, characterize, compute, estimate, and make decisions on the basis of the random return. Practitioners in disciplines as diverse as finance (risk management), computational neuroscience, computational psychiatry, psychology, macroeconomics, and robotics are already using distributional reinforcement learning, paving the way for its expanding applications in mathematical finance, engineering, and the life sciences. More than a mathematical approach, distributional reinforcement learning represents a new perspective on how intelligent agents make predictions and decisions.
    Keywords: Computer Science/Machine Learning & Neural Networks ; thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 12
    facet.materialart.
    Unknown
    Computational Formalism (2023)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-03-23
    Description: How the use of machine learning to analyze art images has revived formalism in art history, presenting a golden opportunity for art historians and computer scientists to learn from one another.Though formalism is an essential tool for art historians, much recent art history has focused on the social and political aspects of art. But now art historians are adopting machine learning methods to develop new ways to analyze the purely visual in datasets of art images. Amanda Wasielewski uses the term “computational formalism” todescribe this use of machine learning and computer vision technique in art historical research. At the same time that art historians are analyzing art images in new ways, computer scientists are using art images for experiments in machine learning and computer vision. Their research, says Wasielewski, would be greatly enriched by the inclusion of humanistic issues.The main purpose in applying computational techniques such as machine learning to art datasets is to automate the process of categorization using metrics such as style, a historically fraught concept in art history. After examining a fifteen-year trajectory in image categorization and art dataset creation in the fields of machine learning and computer vision, Wasielewski considers deep learning techniques that both create and detect forgeries and fakes in art. She investigates examples of art historical analysis in the fields of computer and information sciences, placing this research in the context of art historiography. She also raises questions as which artworks are chosen for digitization, and of those artworks that are born digital, which works gain acceptance into the canon of high art.
    Keywords: Art history ; artificial intelligence ; machine learning ; formalism ; digital humanities ; connoisseurship ; image database ; authentication ; style ; thema EDItEUR::A The Arts::AG The Arts: treatments and subjects::AGA History of art ; thema EDItEUR::3 Time period qualifiers::3M c 1500 onwards to present day::3MN 19th century, c 1800 to c 1899 ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::A The Arts::AF The Arts: art forms::AFK Non-graphic and electronic art forms::AFKV Digital, video and new media arts
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 13
    facet.materialart.
    Unknown
    Actual Causality (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-08
    Description: A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C “actually caused” event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers.
    Keywords: Functional analysis ; probabilities ; probability ; causation ; causality ; causal modeling ; causal model ; model ; complexity ; axiomization ; responsibility ; blame ; explanation ; definitions ; network ; cause ; computation ; dependence ; endogenous variable ; variable ; intervention ; normality ; ordering ; structural equations ; witness ; typicality ; bic Book Industry Communication::H Humanities::HP Philosophy::HPX Popular philosophy ; bic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::Q Philosophy and Religion::QD Philosophy::QDX Popular philosophy ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 14
    facet.materialart.
    Unknown
    Against Reduction (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: Provocative, hopeful essays imagine a future that is not reduced to algorithms. What is human flourishing in an age of machine intelligence, when many claim that the world's most complex problems can be reduced to narrow technical questions? Does more computing make us more intelligent, or simply more computationally powerful? We need not always resist reduction; our ability to simplify helps us interpret complicated situations. The trick is to know when and how to do so. Against Reduction offers a collection of provocative and illuminating essays that consider different ways of recognizing and addressing the reduction in our approach to artificial intelligence, and ultimately to ourselves. Inspired by a widely read manifesto by Joi Ito that called for embracing the diversity and irreducibility of the world, these essays offer persuasive and compelling variations on resisting reduction. Among other things, the writers draw on Indigenous epistemology to argue for an extended “circle of relationships” that includes the nonhuman and robotic; cast “Snow White” as a tale of AI featuring a smart mirror; point out the cisnormativity of security protocol algorithms; map the interconnecting networks of so-called noncommunicable disease; and consider the limits of moral mathematics. Taken together, they show that we should push back against some of the reduction around us and do whatever is in our power to work toward broader solutions.
    Keywords: Artificial intelligence ; Impact of science and technology on society ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::P Mathematics and Science::PD Science: general issues::PDR Impact of science and technology on society
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 15
    facet.materialart.
    Unknown
    Gaussian Processes for Machine Learning (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
    Keywords: Computer science ; Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 16
    facet.materialart.
    Unknown
    Letters, Power Lines, and Other Dangerous Things (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2022-02-21
    Description: An examination of how post-9/11 security concerns have transformed the public view and governance of infrastructure. After September 11, 2001, infrastructures—the mundane systems that undergird much of modern life—were suddenly considered “soft targets” that required immediate security enhancements. Infrastructure protection quickly became the multibillion dollar core of a new and expansive homeland security mission. In this book, Ryan Ellis examines how the long shadow of post-9/11 security concerns have remade and reordered infrastructure, arguing that it has been a stunning transformation. Ellis describes the way workers, civic groups, city councils, bureaucrats, and others used the threat of terrorism as a political resource, taking the opportunity not only to address security vulnerabilities but also to reassert a degree of public control over infrastructure. Nearly two decades after September 11, the threat of terrorism remains etched into the inner workings of infrastructures through new laws, regulations, technologies, and practices. Ellis maps these changes through an examination of three U.S. infrastructures: the postal system, the freight rail network, and the electric power grid. He describes, for example, how debates about protecting the mail from anthrax and other biological hazards spiraled into larger arguments over worker rights, the power of large-volume mailers, and the fortunes of old media in a new media world; how environmental activists leveraged post-9/11 security fears over shipments of hazardous materials to take on the rail industry and the chemical lobby; and how otherwise marginal federal regulators parlayed new mandatory cybersecurity standards for the electric power industry into a robust system of accountability.
    Keywords: Infrastructure ; security ; vulnerability ; risk ; politics ; risk assessment ; 911 ; deregulation ; cybersecurity ; power lines ; electric grid ; USPS ; mail ; anthrax ; transportation networks ; homeland security ; critical infrastructure ; TSA ; regulation ; detection ; securitization ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCS Economic systems & structures ; bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNF Environmental management::RNFY Energy resources
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 17
    facet.materialart.
    Unknown
    Gradient Expectations (2023)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI.Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems.Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today's deep learning. Digging into the connections between predictions and gradients, and their manifestation in the brain and neural networks, is one compelling example of how Downing enriches both our understanding of such relationships and their role in strengthening AI tools. Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms.
    Keywords: Computer Science/Artificial Intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQN Neural networks and fuzzy systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GT Interdisciplinary studies::GTK Cognitive studies
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
  • 18
    facet.materialart.
    Unknown
    How Humans Judge Machines (2022)
    The MIT Press | The MIT Press
    Details
    Publication Date: 2024-04-14
    Description: How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more. How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance? How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions. Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender? César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer to understanding the ethical consequences of AI. Written by César A. Hidalgo, the author of Why Information Grows and coauthor of The Atlas of Economic Complexity (MIT Press), together with a team of social psychologists (Diana Orghian and Filipa de Almeida) and roboticists (Jordi Albo-Canals), How Humans Judge Machines presents a unique perspective on the nexus between artificial intelligence and society. Anyone interested in the future of AI ethics should explore the experiments and theories in How Humans Judge Machines.
    Keywords: A.I. Ethics ; Artificial Intelligence ; Robotics ; Psychology ; Automation ; Future of Work ; Fourth Industrial Revolution ; Algorithmic Bias ; Privacy ; Labor Displacement ; Machine Ethics ; Moral Psychology ; Ethics ; Human Robot Interactions ; Positive Philosophy ; Moral Experiments ; Intention ; Moral Foundations Theory ; Computational Creativity ; Uncertainity ; Fairness ; Bias ; Differential Privacy ; Anonymity ; Wrongness ; Demographics ; Moral Foundations ; Laws or Robotics ; Legal Implications of Robotics ; Bureacracies ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects
    Language: English
    Format: image/jpeg
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    E-BOOK
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...