The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students (...) enrolled in computer science curriculum at Al-Azhar University, Gaza. The results showed a positive impact on the evaluators. (shrink)

I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)

The discipline of ontology has enjoyed a checkered history since 1606, with a significant expansion in recent years. We focus here on those developments in the recent history of philosophy which are most relevant to the understanding of the increased acceptance of ontology, and especially of realist ontology, as a valuable method also outside the discipline of philosophy.

Under the wave of globalization, the ties between countries are getting closer and closer. Based on the differences in the languages of different countries, the importance of English as a universal language is becoming more and more prominent. In the past, English teaching was mainly taught by teachers and students. This mode of English learning is more of theoretical teaching, which has little effect on improving English ability. In the era of intelligence, with the upgrading of technology and the (...) renewal of ideas, interactive English teaching is more accepted by people and becomes a new solution for English teaching. Studying English teaching from the perspective of social cognition, this paper proposes to realize human-computer interaction with the help of advanced science and technology, create an interactive teaching environment, and realize interactive learning in an English environment. This paper designed a control experiment of the experimental group and the control group to verify the impact of human-computer interaction teaching on students’ English performance and investigated students’ performance and teachers’ feelings and their related opinions on human-computer interaction learning. The experimental results of this paper show that human-computer interactive English teaching can help to enhance students’ interest in English learning and improve English expression significantly. (shrink)

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction (...) with their styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms. (shrink)

European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can be analyzed (...) on different levels of organization giving place for variety of possible approaches which converge in this cross-disciplinary and multi-disciplinary research field. Keynotes by Kevin Warwick about re-embodiment of rats’ neurons into robots, Raymond Turner on syntax and semantics in programming languages, Roderic Guigo on Biocomputing Sciences and Francesco Subirada on the past and future of supercomputing presented different topics of philosophical as well as practical aspects of computing. Vonference tracks included: Philosophy of Information (Patrick Allo), Philosophy of Computer Science (Raymond Turner), Computer and Information Ethics (Johnny Søraker and Alison Adam), Computational Approaches to the Mind (Ruth Hagengruber), IT and Cultural Diversity (Jutta Weber and Charles Ess), Crossroads (David Casacuberta), Robotics, AI & Ambient Intelligence (Thomas Roth-Berghofer), Biocomputing, Evolutionary and Complex Systems (Gordana Dodig Crnkovic and Søren Brier), E-learning, E-science and Computer-Supported Cooperative Work (Annamaria Carusi) and Technological Singularity and Acceleration Studies (Amnon Eden). (shrink)

This book provides a sustained and penetrating critique of a wide range of views in modern cognitive science and philosophy of the mind, from Turing's famous test for intelligence in machines to recent work in computational linguistic theory. While discussing many of the key arguments and topics, the authors also develop a distinctive analytic approach. Drawing on the methods of conceptual analysis first elaborated by Wittgenstein and Ryle, the authors seek to show that these methods still have a (...) great deal to offer in the field of the cognitive theory and the philosophy of mind, providing a powerful alternative to many of the positions put forward in the contemporary literature. Amoung the many issues discussed in the book are the following: the Cartesian roots of modern conceptions of mind; Searle's 'Chinese Room' thought experiment; Fodor's 'language of thought' hypothesis; the place of 'folk psychology' in cognitivist thought; and the question of whether any machine may be said to 'think' or 'understand' in the ordinary senses of these words. Wide ranging, up-to-date and forcefully argued, this book represents a major intervention in contemporary debates about the status of cognitive science an the nature of mind. It will be of particular interest to students and scholars in philosophy, psychology, linguistics and computing sciences. (shrink)

Cognitive science is founded on the conjecture that natural intelligence can be explained in terms of computation. Yet, notoriously, there is no consensus among philosophers of cognitive science as to how computation should be characterised. While there are subtle differences between the various accounts of computation found in the literature, the largest fracture exists between those that unpack computation in semantic terms (and hence view computation as the processing of representations) and those, such as that defended by (...) Chalmers (2011), that cleave towards a purely syntactic formulation (and hence view computation in terms of abstract functional organisation). It will be the main contention of this paper that this dispute arises because contemporary computer science is an amalgam of two different historical traditions, each of which has developed its own proprietary conception of computation. Once these historical trajectories have been properly delineated, and the motivations behind the associated conceptions of computation revealed, it becomes a little clearer which should form the foundation for cognitive science. (shrink)

What are the conditions under which groups of agents will perform well across multiple tasks? The author establishes a set of “alignment conditions” that enforce identity of beliefs and desires across agents. These conditions are necessary and sufficient for ensuring that a multiagent system behaves as if controlled by a rational centralized controller. Several widely observed social phenomena can be understood as facilitating the alignment conditions.

La tensión entre fidelidad a la tradición e innovación presente en el pensamiento plotiniano se manifiesta de modo patente en su propuesta metafísica. La ontología expuesta en las Enéadas, en efecto, es un claro ejemplo de la labor exegética mediante la cual Plotino toma las concepciones metafísicas platónico-pitagóricas precedentes y las sintetiza infundiendo nueva vitalidad en ideas antiguas. Para llevar a cabo su exégesis utiliza, incluso, conceptos aristotélicos que integra de un modo peculiar a su pensamiento platonizante. En el presente (...) trabajo, pues, nos proponemos esclarecer el procedimiento interpretativo que Plotino lleva a cabo en la formulación de su doctrina de lo Uno y de la relación entre esta hipóstasis y la Inteligencia. En nuestro análisis examinamos las nociones metafísicas que nuestro filósofo toma como punto de partida y brindamos una interpretación de la transformación que opera sobre ellas para arribar al sistema que dio origen a una nueva corriente de pensamiento platónico. The tension between innovation and fidelity to tradition present in the thought of Plotinus manifests itself clearly in his metaphysical conception. The ontology put forward in the Enneads, in fact, is a fine example of the exegetical work by which our thinker takes the preceding platonic-pythagorean metaphysics and synthesizes it, bringing new vitality into ancient ideas. To accomplish his exegesis he even employs Aristotelian concepts incorporating them in a peculiar way to his Platonizing thought. In the present paper, hence, we intend to elucidate the interpretive procedure that Plotinus carries out to arrive at his conceptions of the One and of the relationship between this hypostasis and Intelligence. In our analysis, we examine the metaphysical notions that our philosopher takes as starting points and we offer an interpretation of the transformation he operates upon them to reach the system that gave birth to a new current of Platonic thought. (shrink)

The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information (...) to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. (shrink)

Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them (...) understand this subject easily and smoothly by analyzing it and explaining it in a systematic way. In this paper, we describe the design of an Intelligent Tutoring System for teaching science for grade seven to help students know the 7 characteristics for living things smoothly. The system provides all topics of living things and generates some questions for each topic and the students should answer these questions correctly to move to the next level. In the result of an evaluation of the ITS, students like the system and they said that it is very useful for them and for their studies. (shrink)

Background Despite the great benefits of intelligent assistive technology (IAT) for dementia care – for example, the enhanced safety and increased independence of people with dementia and their caregivers – its practical adoption is still limited. The social and ethical issues pertaining to IAT in dementia care, shaped by factors such as culture, may explain these limitations. However, most studies have focused on understanding these issues within one cultural setting only. Therefore, the aim of this study was to explore and (...) compare the attitudes of Israeli and German dementia experts toward IAT in dementia care, to contribute to a more cultural-comparative perspective. Methods Semi-structured interviews were conducted with 35 experts (15 Israelis and 20 Germans) in key roles in health and community services for people with dementia as well as in the fields of dementia and IAT (e.g., computer science, electrical/biomedical engineering, ethics, nursing, and gerontology). Thematic content analysis was used to analyze the data. Findings Israeli and German experts identified the same social accelerators in the development and implementation of IAT in dementia care (i.e., changes in family structure and social digitization) and benefits of adopting IAT (e.g., enhancing the safety of people with dementia and increasing their independence). However, there were differences in inhibitor/risk assessments between the two groups. Namely, economic considerations and the cognitive capacity of people with dementia were identified by both groups as inhibitors, while Israeli experts additionally reported stigma and ageism. Whereas both groups agreed that IAT might reduce human connection, and that the technology is not yet reliable enough, German experts highlighted concerns regarding privacy; in contrast, Israeli experts prioritized safety over privacy. Conclusions Our research findings allow for the identification of relevant similarities but also important differences between German and Israeli experts’ perspectives. As such, an important basis has been provided for a more in-depth discussion regarding where, why, and how culturally-sensitive technology development is needed. (shrink)

Reflecting Alan Robinson's fundamental contribution to computational logic, this book brings together seminal papers in inference, equality theories, and logic programming. It is an exceptional collection that ranges from surveys of major areas to new results in more specialized topics. Alan Robinson is currently the University Professor at Syracuse University. Jean-Louis Lassez is a Research Scientist at the IBM Thomas J. Watson Research Center. Gordon Plotkin is Professor of Computer Science at the University of Edinburgh. Contents: Inference. Subsumption, (...) A Sometimes Undervalued Procedure, Larry Wos, Ross Overbeek, and Ewing Lusk. The Markgraf Karl Refutation Procedure, Hans Jurgen Ohlbach and Jorg H. Siekmann. Modal Logic Should Say More than it Does, Melvin Fitting. Interactive Proof Presentation, W. W. Bledsoe. Intelligent Backtracking Revisited, Maurice Bruynooghe. A Science of Reasoning, Alan Bundy. Inductive Inference of Theories from Facts, Ehud Y. Shapiro. Equality. Solving Equations in Abstract Algebras: A Rule-based Survey of Unification, Jean-Pierre Jouannaud and Claude Kirchner. Disunification: A Survey, Hubert Comon. A Case Study of the Completion Procedure: Proving Ring Commutativity Problems, Deepak Kapur and Hantao Zhang. Computations in Regular Rewriting Systems I and II, Girard Huet and JeanJacques Levy. Unification and ML Type Reconstruction, Paris Kanellakis, Harry Mairson, and John Mitchell. Automatic Dimensional Analysis, Mitchell Wand. Logic Programming. Logic Programming Schemes and Their Implementations, Keith Clark. A Near-Horn Prolog for Compilation, Donald Loveland and David Reed. Unfold/Fold Transformations of Logic Programs, P. A. Gardner and J. C. Shepherdson. An Algebraic Representation of Logic Program Computations, Andrea Corradini and Ugo Montanari. Theory of Disjunctive Logic Programs, Jack Minker, Arcot Rajasekar, and Jorge Lobo. Bottom-Up Evaluation of Logic Programs, Jeffrey Naughton and Raghu Ramakrishnan. Absys, the First Logic Programming Language: A View of the Inevitability of Logic Programming, E. W. Elcock. (shrink)

``Neural computing'' is a research field based on perceiving the human brain as an information system. This system reads its input continuously via the different senses, encodes data into various biophysical variables such as membrane potentials or neural firing rates, stores information using different kinds of memories (e.g., short-term memory, long-term memory, associative memory), performs some operations called ``computation'', and outputs onto various channels, including motor control commands, decisions, thoughts, and feelings. We show a natural model of neural computing that (...) gives rise to hyper-computation. Rigorous mathematical analysis is applied, explicating our model's exact computational power and how it changes with the change of parameters. Our analog neural network allows for supra-Turing power while keeping track of computational constraints, and thus embeds a possible answer to the superiority of the biological intelligence within the framework of classical computer science. We further propose it as standard in the field of analog computation, functioning in a role similar to that of the universal Turing machine in digital computation. In particular an analog of the Church-Turing thesis of digital computation is stated where the neural network takes place of the Turing machine. (shrink)

This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being tested (...) by the cognitive psychologists and language researchers in our group, and a computational model of a reader of narrative text is being developed by the AI researchers, based in part on these theories and results and in part on research on knowledge representation and reasoning. This proposal describes the knowledge-representation and natural-language-processing issues involved in the computational implementation of the theory; discusses a contrast between communicative and narrative uses of language and of the relation of the narrative text to the story world it describes; investigates linguistic, literary, and hermeneutic dimensions of our research; presents a computational investigation of subjective sentences and reference in narrative; studies children’s acquisition of the ability to take third-person perspective in their own storytelling; describes the psychological validation of various linguistic devices; and examines how readers develop an understanding of the geographical space of a story. This report is a longer version of a project description submitted to NSF. This document, produced in May 2007, is a L ATEX version of Technical Report 89-07 (Buffalo: SUNY Buffalo Department of Computer Science, August 1989), with slightly.. (shrink)

Science as Salvation discusses the high spiritual ambitions which tend to gather round the notion of science. Officially, science claims only the modest function of establishing facts. Yet people still hope for something much grander from it--namely, the myths by which to shape and support life in an increasingly confusing age. Our faith in science is abused by some scientists whose adolescent fantasies have spilled over into their professional lives. Salvation, immortality, mastery of the universe, humans (...) without bodies, and intelligent self-reproducing computers are just some of the notions and speculations that are now found--not on the pages of science fiction--but on the pages of science itself. The danger is that these concepts are given to a myth-hungry public who turn to science now that religion has lost its ability to create myth. Science as Salvation discusses the function and meaning of such fantasies. Midgley examines the need for and the use of myth in science, and how science and religion are related. She argues that we need to develop a realistic understanding of scientific imagination and its importance. Taking them seriously as symptoms of a genuine myth-hunger, it suggests that the proper function of science may need to include wider perspectives, which would make it plain that such desperate, compensatory dramas are unnecessary. (shrink)

Collective intelligence is much talked about but remains very underdeveloped as a field. There are small pockets in computer science and psychology and fragments in other fields, ranging from economics to biology. New networks and social media also provide a rich source of emerging evidence. However, there are surprisingly few useable theories, and many of the fashionable claims have not stood up to scrutiny. The field of analysis should be how intelligence is organised at large scale—in (...) organisations, cities, nations and networks. The paper sets out some of the potential theoretical building blocks, suggests an experimental and research agenda, shows how it could be analysed within an organisation or business sector and points to the possible intellectual barriers to progress. (shrink)

This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role (...) of language and communication in cognition, the nature of embodied cognition, selective topics in visual cognition, brain connectivity, computation and simulation, social and technological issues within the cognitive sciences, and significant issues in the history of neuroscience. This book will be of interest to both professional researchers and newer students and graduate students in the fields of cognitive science—including computer science, linguistics, philosophy, psychology and neuroscience. The essays are in English and are designed to be as free as possible of technical jargon and therefore accessible to young scholars and to scholars who are new to the cognitive neurosciences. In addition to several entries by single authors, the book contains several interesting roundtables where researchers contribute answers to a central question presented to those in the focus group on one of the core areas listed above. This exciting approach provides a variety of perspectives from across disciplines on topics of current concern in the cognitive sciences. (shrink)

This paper explores how the Leviathan that projects power through nuclear arms exercises a unique nuclearized sovereignty. In the case of nuclear superpowers, this sovereignty extends to wielding the power to destroy human civilization as we know it across the globe. Nuclearized sovereignty depends on a hybrid form of power encompassing human decision-makers in a hierarchical chain of command, and all of the technical and computerized functions necessary to maintain command and control at every moment of the sovereign's existence: this (...) sovereign power cannot sleep. This article analyzes how the form of rationality that informs this hybrid exercise of power historically developed to be computable. By definition, computable rationality must be able to function without any intelligible grasp of the context or the comprehensive significance of decision-making outcomes. Thus, maintaining nuclearized sovereignty necessarily must be able to execute momentous life and death decisions without the type of sentience we usually associate with ethical individual and collective decisions. (shrink)

We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure (...) that algorithmic governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider barriers to legitimate and effective algorithmic governance and the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence. (shrink)

In order to understand history as it has been practised in the twentieth century, we must go back in time. Not necessarily to Herodotus and Thucydides, nor even to the great founding figures of the ages of learning and of the Enlightenment, however enduring their influence. But to those historians who in the course of the nineteenth century brought to its conclusion the radical renewal of knowledge about the past: the means that enabled them to acquire it, arguments which were (...) accepted as proofs, conceptual frameworks supposed to make deeds intelligible, ways of talking about times past - to historians who integrated this knowledge that was formerly split between literature, learned research and theology supplanted by philosophy, around a discipline comparable to philology as much from the epistemological point of view as in terms of status and driven not only by ambition to retain the exclusive right to the term history but also, very early, by that of conquering a superior position in the world of science. (shrink)

The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information (...) to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. (shrink)

Interdisciplinary investigations marry the methods and concerns of different fields. Computer science is the study of precise descriptions of finite processes; semantics is the study of meaning in language. Thus, computational semantics embraces any project that approaches the phenomenon of meaning by way of tasks that can be performed by following definite sets of mechanical instructions. So understood, computational semantics revels in applying semantics, by creating intelligent devices whose broader behavior fits the meanings of utterances, and not just (...) their form. IBM’s Watson (Ferrucci, Brown, Chu-Carroll, Fan, Gondek, Kalyanpur, Lally, Murdock, Nyberg, Prager, Schlaefer & Welty 2010) is a harbinger of the excitement and potential of this technology. (shrink)

Science as Salvationdiscusses the high spiritual ambitions which tend to gather round the notion of science. Officially, science claims only the modest function of establishing facts. Yet people still hope for something much grander from it--namely, the myths by which to shape and support life in an increasingly confusing age. Our faith in science is abused by some scientists whose adolescent fantasies have spilled over into their professional lives. Salvation, immortality, mastery of the universe, humans without (...) bodies, and intelligent self-reproducing computers are just some of the notions and speculations that are now found--not on the pages of science fiction--but on the pages of science itself. The danger is that these concepts are given to a myth-hungry public who turn to science now that religion has lost its ability to create myth. Science as Salvationdiscusses the function and meaning of such fantasies. Midgley examines the need for and the use of myth in science, and how science and religion are related. She argues that we need to develop a realistic understanding of scientific imagination and its importance. Taking them seriously as symptoms of a genuine myth-hunger, it suggests that the proper function of science may need to include wider perspectives, which would make it plain that such desperate, compensatory dramas are unnecessary. (shrink)

This text enables readers to understand human intelligence from a variety of standpoints, such as psychology, anthropology, computational science, sociology, and philosophy. Readers will gain a comprehensive understanding of the concept of intelligence and how ideas about it have evolved and are continuing to evolve. Much of the present confusion surrounding the concept of intelligence stems from our having looked at it from these different standpoints without considering how they relate to each other or how they (...) might be combined into a unified view that goes beyond the boundaries of a particular discipline. (shrink)

On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of (...) intelligence. This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed. (shrink)

This book examines the interface between mathematics and applied sciences. The editor examines the present and future needs for the interaction between various science and engineering areas. This edited book brings together the cutting-edge research on mathematics, combining various fields of science and engineering. The book begins with an introduction to computing and modeling. Next, computation and modeling trends are covered, along with chapters on structural static and vibration problems, heat conduction and diffusion problems, and fluid dynamics problems. (...) Soft computing and machine intelligence based modeling are also discussed, along with bio medical problems. The book concludes with a chapter on modeling in mining, electrical, electronics, and chemical problems. This book is a reference for students and researchers in various fields of engineering such as computer, mechanical, civil, aerospace, electrical, and chemical, as well as and other sciences such as applied mathematics, physics, chemistry, and life sciences. (shrink)

The technological singularity refers to a hypothetical scenario in which technological advances virtually explode. The most popular scenario is the creation of super-intelligent algorithms that recursively create ever higher intelligences. It took many decades for these ideas to spread from science fiction to popular science magazines and finally to attract the attention of serious philosophers. David Chalmers' (JCS 2010) article is the first comprehensive philosophical analysis of the singularity in a respected philosophy journal. The motivation of my article (...) is to augment Chalmers' and to discuss some issues not addressed by him, in particular what it could mean for intelligence to explode. In this course, I will (have to) provide a more careful treatment of what intelligence actually is, separate speed from intelligence explosion, compare what super-intelligent participants and classical human observers might experience and do, discuss immediate implications for the diversity and value of life, consider possible bounds on intelligence, and contemplate intelligences right at the singularity. (shrink)

In this book the editors invited prominent researchers with different perspectives and deep insights into the various facets of the relationship between reality and representation in the following three classes of agent: in humans, in other living beings, and in machines. -/- The book enriches our views on representation and deepens our understanding of its different aspects, a question that connects philosophy, computer science, logic, anthropology, psychology, sociology, neuroscience, linguistics, information and communication science, systems theory and engineering, (...) computability, cybernetics, synthetic biology, and bioinformatics biosemiotics. This book will be relevant to researchers in these fields. (shrink)

In this carefully argued critique, Steven Horst pronounces the theory deficient.

Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these (...) days, and to date they have all been equally plausible and equally successful. And, just to be explicit, I do not mean “IQ” by “intelligence.” I am using “intelligence” in the way AI uses it: as a semi-techical term referring to a general property of all intelligent systems, animal (including humans), or machine, alike.). (shrink)

A great deal of attention has been paid by philosophers to the use of computers in the modelling of human cognitive capacities and in the construction of intelligent artifacts. This emphasis has tended to obscure the fact that most of the high-level computing power in science is deployed in what appears to be a much less exciting activity: solving equations. This apparently mundane set of applications reflects the historical origins of modem computing, in the sense that most of the (...) early computers in Britain and the U.S. were devices built to numerically attack mathematical problems that were hard, if not impossible, to solve non-numerically, especially in the areas of ballistics and fluid dynamics. The latter area was especially important for the development of atomic weapons at Los Alamos, and it is still true that a large portion of the supercomputing capacity of the United States is concentrated at weapons development laboratories such as Los Alamos and Lawrence Livermore. (shrink)

This paper examines how the Polish communist intelligence service attempted to recruit professor Stefan Węgrzyn, who was a prominent specialist on automatic control and computer science in post-war Poland. Eventually, Węgrzyn’s refusal to cooperate with the Polish spy agency, together with his profound relationship with French scientist and servomechanism expert Jean Charles Gille, made them both targets of surveillance orchestrated by the communist security apparatus. In the broader context of human-intelligence studies, this case study involves the (...) problem of moral ambiguity. We experience informative examples of scientists, who often – not only during the Cold War – have had to choose between commitment to the rules of the academic world, along with its openness and transparency on the one hand, and patriotism including an ethos of secrecy for the sake of the homeland’s prosperity, on the other hand. (shrink)

In 1982, when computers were just becoming widely available, I was a graduate student beginning my work with Clark Glymour on a PhD thesis entitled: “Causality in the Social Sciences.” Dazed and confused by the vast philosophical literature on causation, I found relative solace in the clarity of Structural Equation Models (SEMs), a form of statistical model used commonly by practicing sociologists, political scientists, etc., to model causal hypotheses with which associations among measured variables might be explained. The statistical literature (...) around SEMs was vast as well, but Clark had extracted from it a particular kind of evidential constraint first studied by Charles Spearman at the beginning of the 20th century, the “vanishing tetrad difference.”1 As it turned out, certain kinds of causal structures entailed these constraints, and others did not. Spearman used this lever to argue for the existence of a single, general intelligence factor, the infamous g (Spearman, 1904). (shrink)

The use of forward models is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model account, forward models lie at the heart of all forms of perception and action. We compare these neighbouring (...) but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches. (shrink)

Intelligent design advocate William Dembski has introduced a measure of information called “complex specified information”, or CSI. He claims that CSI is a reliable marker of design by intelligent agents. He puts forth a “Law of Conservation of Information” which states that chance and natural laws are incapable of generating CSI. In particular, CSI cannot be generated by evolutionary computation. Dembski asserts that CSI is present in intelligent causes and in the flagellum of Escherichia coli, and concludes that neither have (...) natural explanations. In this paper, we examine Dembski’s claims, point out significant errors in his reasoning, and conclude that there is no reason to accept his assertions. (shrink)