The quality of doctoral-level chemistry (N=145), computer science (N=58), geoscience (N=91), mathematics (N=115), physics (N=123), and statistics/biostatistics (N=64) programs at United States universities was assessed, using 16 measures. These measures focused on variables related to: program size; characteristics of graduates; reputational factors (scholarly quality of faculty, effectiveness of programs in educating research scholars/scientists, improvement in program quality during the last 5 years); university library size; research support; and publication records. Chapter I discusses prior attempts to assess quality in graduate (...) education, development of the study plans, and the selection of disciplines and programs to be evaluated. Chapter II discusses the methodology used, focusing on each of the assessment measures. Chapters III to VIII present, respectively, findings from the analyses of the chemistry, computer science, geoscience, mathematics, physics, and statistics/biostatistics programs. Chapter IX includes a summary of results, correlations among measures, several additional analyses, and suggestions for future studies. Among the findings reported are those indicating that mathematics programs had, on the average, the largest number of faculty (N=33) in December 1980 followed closely by physics (N=28) and chemistry (N=23), and that 80 percent of computer science students had job commitments by graduation. (Survey instruments and supporting documentation are included in appendices.) (JN). (shrink)

This paper makes a novel linkage between the multiple-computations theorem in philosophy of mind and Landauer’s principle in physics. The multiple-computations theorem implies that certain physical systems implement simultaneously more than one computation. Landauer’s principle implies that the physical implementation of “logically irreversible” functions is accompanied by minimal entropy increase. We show that the multiple-computations theorem is incompatible with, or at least challenges, the universal validity of Landauer’s principle. To this end we provide accounts of both ideas in (...) terms of low-level fundamental concepts in statistical mechanics, thus providing a deeper understanding of these ideas than their standard formulations given in the high-level terms of thermodynamics and cognitive science. Since Landauer’s principle is pivotal in the attempts to derive the universal validity of the second law of thermodynamics in statistical mechanics, our result entails that the multiple-computations theorem has crucial implications with respect to the second law. Finally, our analysis contributes to the understanding of notions, such as “logical irreversibility,” “entropy increase,” “implementing a computation,” in terms of fundamental physics, and to resolving open questions in the literature of both fields, such as: what could it possibly mean that a certain physical process implements a certain computation. (shrink)

This article reformulates the theory of computable physical models, previously introduced by the author, as a branch of applied model theory in first-order logic. It provides a semantic approach to the philosophy of science that incorporates aspects of operationalism and Popper’s degrees of falsifiability.

Realism about computation is the view that whether or not a particular physical system is performing a particular computation is at least sometimes a mindindependent feature of reality. The caveat ’at least sometimes’ is necessary here because a realist about computation need not believe that all instances of computation should be realistically construed. The computational theory of mind presupposes realism about computation. If whether or not the human nervous system implements particular computations is not a (...) natural fact about the world that is independent of whether we represent it as doing so, then the computational theory of mind fails to naturalise the mind. Realism about computation is also presupposed by attempts to use computational principles such as Landauer’s Principle to dispel Maxwell’s Demon. Realism about computation has been challenged by Hilary Putnam and John Searle among others. Various arguments have been put forward purporting to show that any physical system of sufficient complexity trivially implements all computations. Ladyman et al. offer a precisification and general proof Landauer’s Principle. In order to do this they present an analysis of what it is for a physical process to implement a logical transformation. In this paper, their analysis is explained and its implications for realism about computation and the use of Landauer’s Principle in foundational debates is assessed. (shrink)

The simulation hypothesis has recently excited renewed interest, especially in the physics and philosophy communities. However, the hypothesis specifically concerns {computers} that simulate physical universes, which means that to properly investigate it we need to couple computer science theory with physics. Here I do this by exploiting the physical Church-Turing thesis. This allows me to introduce a preliminary investigation of some of the computer science theoretic aspects of the simulation hypothesis. In particular, building on Kleene's second recursion theorem, (...) I prove that it is mathematically possible for us to be in a simulation that is being run on a computer \textit{by us}. In such a case, there would be two identical instances of us; the question of which of those is ``really us'' is meaningless. I also show how Rice's theorem provides some interesting impossibility results concerning simulation and self-simulation; briefly describe the philosophical implications of fully homomorphic encryption for (self-)simulation; briefly investigate the graphical structure of universes simulating universes simulating universes, among other issues. I end by describing some of the possible avenues for future research that this preliminary investigation reveals. (shrink)

The explosive growth in computational power over the past several decades offers new tools and opportunities for economists. This handbook volume surveys recent research on Agent-based Computational Economics (ACE), the computational study of economic processes modeled as open-ended dynamic systems of interacting agents. Empirical referents for “agents” in ACE models can range from individuals or social groups with learning capabilities to physical world features with no cognitive function. Topics covered include: learning; empirical validation; network economics; social dynamics; financial markets; innovation (...) and technological change; organizations; market design; automated markets and trading agents; political economy; social-ecological systems; computational laboratory development; and general methodological issues. (shrink)

This Element has three main aims. First, it aims to help the reader understand the concept of computation that Turing developed, his corresponding results, and what those results indicate about the limits of computational possibility. Second, it aims to bring the reader up to speed on analyses of computation in physical systems which provide the most general characterizations of what it takes for a physical system to be a computational system. Third, it aims to introduce the reader to (...) some different kinds of quantum computers, describe quantum speedup, and present some explanation sketches of quantum speedup. If successful, this Element will equip the reader with a basic knowledge necessary for pursuing these topics in more detail. (shrink)

Computers provide tools suprisingly effective in analyzing physical processes. The interaction of analytical and computer methods of physical research has been synergistic. Examples are given of the conceptual advances which have been spurred by the interaction of computer and classical analysis. It is argued that a new age in physical research is beginning and that the power of computer tools has scarcely been tapped.

There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.

The problem of multiple-computations discovered by Hilary Putnam presents a deep difficulty for functionalism (of all sorts, computational and causal). We describe in out- line why Putnam’s result, and likewise the more restricted result we call the Multiple- Computations Theorem, are in fact theorems of statistical mechanics. We show why the mere interaction of a computing system with its environment cannot single out a computation as the preferred one amongst the many computations implemented by the system. We explain why (...) nonreductive approaches to solving the multiple- computations problem, and in particular why computational externalism, are dualistic in the sense that they imply that nonphysical facts in the environment of a computing system single out the computation. We discuss certain attempts to dissolve Putnam’s unrestricted result by appealing to systems with certain kinds of input and output states as a special case of computational externalism, and show why this approach is not workable without collapsing to behaviorism. We conclude with some remarks about the nonphysical nature of mainstream approaches to both statistical mechanics and the quantum theory of measurement with respect to the singling out of partitions and observables. (shrink)

Unifying the Universe: The Physics of Heaven and Earth presents a non-technical approach to physics for the lay-science enthusiast. This popular textbook, which evolved from a conceptual course at Cornell University, is intended for non-science undergraduate students taking their first physics module. This second edition maintains its unique approach in crossing boundaries between physics and humanities, with connections to art, poetry, history, and philosophy. It explores how the process of scientific thought is inextricably linked with cultural, (...) creative, and aesthetic aspects of human endeavor, opening the readers up to new ways of looking at the world. The text has been fully updated throughout to address current and exciting new topics in the field, such as exo-planets, the accelerating Universe, dark matter, dark energy, gravitational waves, super-symmetry, string theory, big bang cosmology, and the Higgs boson. There is also an entirely new chapter on the Quantum World, which connects the fascinating topics of quantum entanglement and quantum computing. Key Features: Provides a solid, yet accessible, background to basic physics without complex mathematics Uses a human interest approach to show how science is significant for more than its technological consequences Discusses the arts and philosophies of historical periods that are pertinent to the subject. (shrink)

The intuition guiding the de…nition of computation has shifted over time, a process that is re‡ected in the changing formulations of the Church-Turing thesis. The theory of computation began with logic and gradually moved to the capacity of …nite automata. Consequently, modern computer models rely on general physical principles, with quantum computers representing the extreme case. The paper discusses this development, and the challenges to the Church-Turing thesis in its physical form, in particular, Kieu’s quantum computer and relativistic (...) hyper-computation. Finally, the robustness of the boundary between polynomial and exponential time complexity is considered in connection with quantum computers and quantum information theory. (shrink)

Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these (...) questions. Justifying the role of computation requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that computation can specify general patterns of causal organization, and mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science. (shrink)

This paper presents several observations on the connections between information, physics, and computation. In particular, the computing power of quantum computers is examined. Quantum theory is characterized by superimposed states and nonlocal interactions. It is argued that recently studied quantum computers, which are based on local interactions, cannot simulate quantum physics.

The prelims comprise: Introduction Programs and Theories Finite Digital Physics Transfinite Digital Physics The Physics of Computation Conclusion.

Representation is typically taken to be importantly separate from its physical implementation. This is exemplified in Marr’s three-level framework, widely cited and often adopted in neuroscience. However, the separation between representation and physical implementation is not a necessary feature of information-processing systems. In particular, when it comes to analog computational systems, Marr’s representational/algorithmic level and implementational level collapse into a single level. Insofar as analog computation is a better way of understanding neural computation than other notions, Marr’s three-level (...) framework must then be amended into a two-level framework. However, far from being a problem or limitation, this sheds lights on how to understand physical media as being representational, but without a separate, medium-independent representational level. (shrink)

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and (...) sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems. (shrink)

This paper examines several issues related to information, speed of computation, and simulation of a physical process. It is argued that mental processes proceed at a rate close to the optimal based on thermodynamic considerations. Problems related to the simulation of a quantum mechanical system on a computer are reviewed. Parallels are drawn between biological and adaptive quantum systems.

This book is a state-of-the-art review on the Physics of Emergence. Foreword v Gregory J. Chaitin Preface vii Ignazio Licata Emergence and Computation at the Edge of Classical and Quantum Systems 1 Ignazio Licata Gauge Generalized Principle for Complex Systems 27 Germano Resconi Undoing Quantum Measurement: Novel Twists to the Physical Account of Time 61 Avshalom C. Elitzur and Shahar Dolev Process Physics: Quantum Theories as Models of Complexity 77 Kirsty Kitto A Cross-disciplinary Framework for the Description (...) of Contextually Mediated Change 109 Liane Gabora and Diederik Aerts Quantum-like Probabilistic Models Outside Physics 135 Andrei Khrennikov Phase Transitions in Biological Matter 165 Eliano Pessa Microcosm to Macrocosm via the Notion of a Sheaf (Observers in Terms of t-topos) 229 Goro Kato The Dissipative Quantum Model of Brain and Laboratory Observations 233 Walter J. Freeman and Giuseppe Vitiello Supersymmetric Methods in the Traveling Variable: Inside Neurons and at the Brain Scale 253 H.C. Rosu, O. Cornejo-Perez, and J.E. Perez-Terrazas Turing Systems: A General Model for Complex Patterns in Nature 267 R.A. Barrio Primordial Evolution in the Finitary Process Soup 297 Olof Gornerup and James P. Crutchfield Emergence of Universe from a Quantum Network 313 Paola A. Zizzi Occam's Razor Revisited: Simplicity vs. Complexity in Biology 327 Joseph P. Zbilut Order in the Nothing: Autopoiesis and the Organizational Characterization of the Living 339 Leonardo Bich and Luisa Damiano Anticipation in Biological and Cognitive Systems: The Need for a Physical Theory of Biological Organization 371 Graziano Terenzi How Uncertain is Uncertainty? 389 Tibor Vamos Archetypes, Causal Description and Creativity in Natural World 405 Leonardo Chiatti . (shrink)

I articulate and defend a new theory of what it is for a physical system to implement an abstract computational model. According to my descriptivist theory, a physical system implements a computational model just in case the model accurately describes the system. Specifically, the system must reliably transit between computational states in accord with mechanical instructions encoded by the model. I contrast my theory with an influential approach to computational implementation espoused by Chalmers, Putnam, and others. I deploy my theory (...) to illuminate the relation between computation and representation. I also rebut arguments, propounded by Putnam and Searle, that computational implementation is trivial. (shrink)

_dualism_ (consciousness lies outside knowable science), _emergence_ (consciousness arises as a novel property from complex computational dynamics in the brain), and some form of _panpsychism_, _pan-protopsychism, or pan-experientialism_ (essential features or precursors of consciousness are fundamental components of reality which are accessed by brain processes). In addition to 1) the problem of subjective experience, other related enigmatic features of consciousness persist, defying technological and philosophical inroads. These include 2) the “binding problem”—how disparate brain activities give rise to a unified sense (...) of “self” or unified conscious content. Temporal synchrony—brain-wide coherence of neural membrane electrical activities—is often assumed to accomplish binding, but _what_ is being synchronized? What is being coherently bound? Another enigmatic feature is 3) the transition from pre-conscious processes to consciousness itself. Most neuroscientists agree that consciousness is the “tip of an iceberg”, that the vast majority of brain activities is. (shrink)

This textbook carefully develops the main ideas and techniques of statistical and thermal physics and is intended for upper-level undergraduate courses. The authors each have more than thirty years' experience in teaching, curriculum development, and research in statistical and computational physics. Statistical and Thermal Physics begins with a qualitative discussion of the relation between the macroscopic and microscopic worlds and incorporates computer simulations throughout the book to provide concrete examples of important conceptual ideas. Unlike many contemporary texts (...) on thermal physics, this book presents thermodynamic reasoning as an independent way of thinking about macroscopic systems. Probability concepts and techniques are introduced, including topics that are useful for understanding how probability and statistics are used. Magnetism and the Ising model are considered in greater depth than in most undergraduate texts, and ideal quantum gases are treated within a uniform framework. Advanced chapters on fluids and critical phenomena are appropriate for motivated undergraduates and beginning graduate students. Integrates Monte Carlo and molecular dynamics simulations as well as other numerical techniques throughout the text Provides self-contained introductions to thermodynamics and statistical mechanics Discusses probability concepts and methods in detail Contains ideas and methods from contemporary research Includes advanced chapters that provide a natural bridge to graduate study Features more than 400 problems Programs are open source and available in an executable cross-platform format Solutions manual. (shrink)

. The origin and history of Landauer’s principle is traced through the development of the thermodynamics of computation at IBM from 1959 to 1982. This development was characterized by multiple conceptual shifts: memory came to be seen not as information storage, but as delayed information transmission; information itself was seen not as a disembodied logical entity, but as participating in the physical world; and logical irreversibility was connected with physical, thermodynamic, irreversibility. These conceptual shifts were characterized by an ambivalence (...) opposing strong metaphysical claims to practical considerations. Three sorts of practical considerations are discussed. First, these conceptual shifts engaged materials central to IBM’s business practice. Second, arguments for metaphysical certainties were made with reference to the practical functioning of typical computers. Third, arguments for metaphysical certainties were made in the context of establishing the thermodynamics of information as a sub-discipline of physics. (shrink)

In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation (...) of models of computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)

Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question ‘What does a particular neuronal system do?’ is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon (...) lends some support to the idea that a single neuronal structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation. (shrink)

A single physical process may often be described equally well as computing several different mathematical functions—none of which is explanatorily privileged. How, then, should the computational identity of a physical system be determined? Some computational mechanists hold that computation is individuated only by either narrow physical or functional properties. Even if some individuative role is attributed to environmental factors, it is rather limited. The computational semanticist holds that computation is individuated, at least in part, by semantic properties. She (...) claims that the mechanistic account lacks the resources to individuate the computations performed by some systems, thereby leaving interesting cases of computational indeterminacy unaddressed. This article examines some of these views, and claims that more cases of computational indeterminacy can be addressed, if the system-environment interaction plays a greater role in individuating computations. A new, long-arm functional strategy for individuating computation is advanced. (shrink)

The mainstream view in cognitive science is that computation lies at the basis of and explains cognition. Our analysis reveals that there is no compelling evidence or argument for thinking that brains compute. It makes the case for inverting the explanatory order proposed by the computational basis of cognition thesis. We give reasons to reverse the polarity of standard thinking on this topic, and ask how it is possible that computation, natural and artificial, might be based on cognition (...) and not the other way around. (shrink)

In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad (...) variation of models of computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)

This chapter has two goals. The first is to explain concepts associated with information and computation in physical terms. The other goal of this chapter is to analyze concepts in physics like space, time, and causality in information-theoretic and computational terms.

Gualtiero Piccinini articulates and defends a mechanistic account of concrete, or physical, computation. A physical system is a computing system just in case it is a mechanism one of whose functions is to manipulate vehicles based solely on differences between different portions of the vehicles according to a rule defined over the vehicles. Physical Computation discusses previous accounts of computation and argues that the mechanistic account is better. Many kinds of computation are explicated, such as digital (...) vs. analog, serial vs. parallel, neural network computation, program-controlled computation, and more. Piccinini argues that computation does not entail representation or information processing although information processing entails computation. Pancomputationalism, according to which every physical system is computational, is rejected. A modest version of the physical Church-Turing thesis, according to which any function that is physically computable is computable by Turing machines, is defended. (shrink)

In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon’s perspective, the embodied view on cognition seems natural but (...) it is nowhere near as critical as its proponents suggest. The only point of difference between Simon and embodied cognition is the significance of body-based off-line cognition; however, it will be argued that it is notoriously over-appreciated in the current debate. The new mechanistic view on explanation suggests that even if it is critical to situate a mechanism in its environment and study its physical composition, or realization, it is also stressed that not all detail counts, and that some bodily features of cognitive systems should be left out from explanations. (shrink)

A skeptical worry known as ‘the indeterminacy of computation’ animates much recent philosophical reflection on the computational identity of physical systems. On the one hand, computational explanation seems to require that physical computing systems fall under a single, unique computational description at a time. On the other, if a physical system falls under any computational description, it seems to fall under many simultaneously. Absent some principled reason to take just one of these descriptions in particular as relevant for computational (...) explanation, widespread failure of computational explanation would appear to follow. This paper advances a new solution to the indeterminacy of computation. Very roughly, I argue that the computational identity of a physical system is determinate relative to a contextually specified way of regarding that system computationally—known as a labelling scheme. When a system simultaneously implements multiple computations, it does so relative to different labelling schemes. But relative to a fixed labelling scheme, a physical system has a unique computational identity. I argue that this relativistic conception of computational identity vindicates computational explanation in the face of simultaneous implementation. (shrink)

In this paper, we pursue three general aims: (I) We will define a notion of fundamental opacity and ask whether it can be found in High Energy Physics (HEP), given the involvement of machine learning (ML) and computer simulations (CS) therein. (II) We identify two kinds of non-fundamental, contingent opacity associated with CS and ML in HEP respectively, and ask whether, and if so how, they may be overcome. (III) We address the question of whether any kind of opacity, (...) contingent or fundamental, is unique to ML or CS, or whether they stand in continuity to kinds of opacity associated with other scientific research. (shrink)

Under what conditions does a physical system implement or realize a computation? Structuralism about computational implementation, espoused by Chalmers and others, holds that a physical system realizes a computation just in case the system instantiates a pattern of causal organization isomorphic to the computation’s formal structure. I argue against structuralism through counter-examples drawn from computer science. On my opposing view, computational implementation sometimes requires instantiating semantic properties that outstrip any relevant pattern of causal organization. In developing my (...) argument, I defend anti-individualism about computational implementation: relations to the social environment sometimes help determine whether a physical system realizes a computation. 1 The Physical Realization Relation2 Semantics and Computational Implementation3 Conforming to Instructions4 Implementing a Computer Program4.1 The denotational semantics of Scheme4.2 Worries about intentionality4.3 Worries about the natural numbers5 Implementing a Machine Model6 Bounded Structuralism7 Triviality Arguments8 Anti-individualism about Computational Implementation. (shrink)

1. The Physical Church-Turing Thesis. Physicists often interpret the Church-Turing Thesis as saying something about the scope and limitations of physical computing machines. Although this was not the intention of Church or Turing, the Physical Church Turing thesis is interesting in its own right. Consider, for example, Wolfram’s formulation: One can expect in fact that universal computers are as powerful in their computational capabilities as any physically realizable system can be, that they can simulate any physical system . . . (...) No physically implementable procedure could then shortcut a computationally irreducible process. (Wolfram 1985) Wolfram’s thesis consists of two parts: (a) Any physical system can be simulated (to any degree of approximation) by a universal Turing machine (b) Complexity bounds on Turing machine simulations have physical significance. For example, suppose that the computation of the minimum energy of some system of n particles takes at least exponentially (in n) many steps. Then the relaxation time of the actual physical system to its minimum energy state will also take exponential time. (shrink)

This book constitutes the refereed proceedings of the 7th Conference on Computability in Europe, CiE 2011, held in Sofia, Bulgaria, in June/July 2011. The 22 revised papers presented together with 11 invited lectures were carefully reviewed and selected with an acceptance rate of under 40%. The papers cover the topics computability in analysis, algebra, and geometry; classical computability theory; natural computing; relations between the physical world and formal models of computability; theory of transfinite computations; and computational linguistics.

The semantic view of computation is the claim that semantic properties play an essential role in the individuation of physical computing systems such as laptops and brains. The main argument for the semantic view rests on the fact that some physical systems simultaneously implement different automata at the same time, in the same space, and even in the very same physical properties. Recently, several authors have challenged this argument. They accept the premise of simultaneous implementation but reject the semantic (...) conclusion. In this paper, I aim to explicate the semantic view and to address these objections. I first characterize the semantic view and distinguish it from other, closely related views. Then, I contend that the master argument for the semantic view survives the counter-arguments against it. One counter-argument is that computational individuation is not forced to choose between the implemented automata but rather always picks out a more basic computational structure. My response is that this move might undermine the notion of computational equivalence. Another counter-argument is that while computational individuation is forced to rely on extrinsic features, these features need not be semantic. My reply is that the semantic view better accounts for these extrinsic features than the proposed non-semantic alternatives. (shrink)

In this paper I argue that whether or not a computer can be built that passes the Turing test is a central question in the philosophy of mind. Then I show that the possibility of building such a computer depends on open questions in the philosophy of computer science: the physical Church-Turing thesis and the extended Church-Turing thesis. I use the link between the issues identified in philosophy of mind and philosophy of computer science to respond to a prominent argument (...) against the possibility of building a machine that passes the Turing test. Finally, I respond to objections against the proposed link between questions in the philosophy of mind and philosophy of computer science. (shrink)

This article tells the story of Ed Fredkin, a pilot, programmer, engineer, hardware designer and entrepreneur, whose work inside and outside academia has influenced major developments in computer science and in the foundations of theoretical physics for the past fifty years.

This paper offers a review of Giuseppe Primero’s (2020) book “On the foundations of computing”_._ Mathematical, engineering, and experimental foundations of the science of computing are examined under the light of the notions of formal, physical, and experimental computational validity provided by the author. It is challenged the thesis that experimental computational validity can be defined only for the algorithmic method and not for the software development process. The notions of computational hypothesis and computational experiment provided by Primiero (2020) are (...) extended to the case of software development. Finally, it is highlighted how the hypothetical-deductive method is involved in the practice of using models to corroborate computational hypotheses in software testing. As a concluding remark, it is underlined how defining experimental computational validity in the context of software development offers a sound experimental foundation to the science of computing. (shrink)

This paper offers an account of what it is for a physical system to be a computing mechanism—a mechanism that performs computations. A computing mechanism is any mechanism whose functional analysis ascribes it the function of generating outputs strings from input strings in accordance with a general rule that applies to all strings. This account is motivated by reasons that are endogenous to the philosophy of computing, but it may also be seen as an application of recent literature on mechanisms. (...) The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. This makes it ideal for grounding the comparison and assessment of computational theories of mind and brain. (shrink)

I survey in this article the practical uses of computers in philosophy: except for logic, computers have not yet noticeably improved the quality of philosophizing, research, or pedagogy. They have made work easier. My main interest, however, is in the “substantive” impact that computers may have on philosophical problems, especially in metaphysics. I argue that logic, the notion of decidability, and the theory of computation all predated and did not require modern digital computers. In the philosophy of mind, there (...) has been a persistent conflation of computationalism and physicalism. The two theses can and should be separated. Finally, I suggest that we see glimpses of a new metaphysics based on information and information transformations that goes far beyond the well‐trodden mind‐brain debates. (shrink)

The phenomenon of consciousness has always been a central question for philosophers and scientists. Emerging in the past decade are new approaches to the understanding of consciousness in a scientific light. This book presents a series of essays by leading thinkers giving an account of the current ideas prevalent in the scientific study of consciousness. The value of the book lies in the discussion of this interesting though complex subject from different points of view ranging from physics, computer science (...) to the cognitive sciences. Reviews of controversial ideas related to the philosophy of mind from western and eastern sources including classical Indian first person methodologies provide a breadth of coverage that has seldom been attempted in a book before. Additionally, chapters relating to the new approaches in computational modelling of higher order cognitive function and consciousness are included. The book is of great value for established as well as young researchers from a wide cross-section of interdisciplinary scientific backgrounds, aiming to pursue research in this field, as well as an informed public. * Presents the latest developments in the scientific study of consciousness * Critically reviews different theoretical and philosophical explanations related to the subject * An important book for both students and researchers in designing research projects on consciousness. (shrink)