Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three‐dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibiting positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputational bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...) Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. We show that every recursively enumerable random real dominates all other recursively enumerable reals. We conclude that the recursively enumerable random reals are exactly the Ω-numbers [G. J. Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. Second, we show that the sets in a universal Martin-Lof test for randomness have random measure, and every recursively enumerable random number is the sum of the measures represented in a universal Martin-Lof test. (shrink)

This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus (...) presents the state of the art in the area. (shrink)

It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing (...) argument. I discuss some objections and reject the view that computer simulations produce knowledge because they are experiments. I conclude by comparing thought experiments and computer simulations, assuming that both are arguments. (shrink)

This essay provides a critique of mainstream computer ethics and argues for the importance of a complementary approach called disclosive computer ethics, which is concerned with the moral deciphering of embedded values and norms in computer systems, applications and practices. Also, four key values are proposed as starting points for disclosive studies in computer ethics: justice, autonomy, democracy and privacy. Finally, it is argued that research in disclosive computer ethics should be multi-level and interdisciplinary, distinguishing (...) between a disclosure level, a theoretical level, and an an application level. (shrink)

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation (...) of the ITS was done by a group of students and teachers. The results were acceptable. (shrink)

Whereas computer simulations involve no direct physical interaction between the machine they are run on and the physical systems they are used to investigate, they are often used as experiments and yield data about these systems. It is commonly argued that they do so because they are implemented on physical machines. We claim that physicality is not necessary for their representational and predictive capacities and that the explanation of why computer simulations generate desired information about their target system (...) is only to be found in the detailed analysis of their semantic levels. We provide such an analysis and we determine the actual consequences of physical implementation for simulations. (shrink)

There are a variety of topics in the philosophy of science that need to be rethought, in varying degrees, after one pays careful attention to the ways in which computer simulations are used in the sciences. There are a number of conceptual issues internal to the practice of computer simulation that can benefit from the attention of philosophers. This essay surveys some of the recent literature on simulation from the perspective of the philosophy of science and argues that (...) philosophers have a lot to learn by paying closer attention to the practice of simulation. (shrink)

The question of where, between theory and experiment, computer simulations (CSs) locate on the methodological map is one of the central questions in the epistemology of simulation (cf. Saam Journal for General Philosophy of Science, 48, 293–309, 2017). The two extremes on the map have them either be a kind of experiment in their own right (e.g. Barberousse et al. Synthese, 169, 557–574, 2009; Morgan 2002, 2003, Journal of Economic Methodology, 12(2), 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; (...) Morrison 2015; Massimi and Bhimji Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 51, 71–81, 2015; Parker Synthese, 169, 483–496, 2009) or just an argument executed with the aid of a computer (e.g. Beisbart European Journal for Philosophy of Science, 2, 395–434, 2012; Beisbart and Norton International Studies in the Philosophy of Science, 26, 403–422, 2012). There exist multiple versions of the first kind of position, whereas the latter is rather unified. I will argue that, while many claims about the ‘experimental’ status of CSs seem unjustified, there is a variant of the first position that seems preferable. In particular I will argue that while CSs respect the logic of (deductively valid) arguments, they neither agree with their pragmatics nor their epistemology. I will then lay out in what sense CSs can fruitfully be seen as experiments, and what features set them apart from traditional experiments nonetheless. I conclude that they should be seen as surrogate experiments, i.e. experiments executed consciously on the wrong kind of system, but with an exploitable connection to the system of interest. Finally, I contrast my view with that of Beisbart (European Journal for Philosophy of Science, 8, 171–204, 2018), according to which CSs are surrogates for experiments, arguing that this introduces an arbitrary split between CSs and other kinds of simulations. (shrink)

The article discusses the use of algorithmic models in finance (algo or high frequency trading). Algo trading is widespread but also somewhat controversial in modern financial markets. It is a form of automated trading technology, which critics claim can, among other things, lead to market manipulation. Drawing on three cases, this article shows that manipulation also can happen in the reverse way, meaning that human traders attempt to make algorithms ‘make mistakes’ by ‘misleading’ them. These attempts to manipulate are very (...) simple and immediately transparent to humans. Nevertheless, financial regulators increasingly penalize such attempts to manipulate algos. The article explains this as an institutionalization of algo trading, a trading practice which is vulnerable enough to need regulatory protection. (shrink)

This article explores some of the roles of computer simulation in measurement. A model-based view of measurement is adopted and three types of measurement—direct, derived, and complex—are distinguished. It is argued that while computer simulations on their own are not measurement processes, in principle they can be embedded in direct, derived, and complex measurement practices in such a way that simulation results constitute measurement outcomes. Atmospheric data assimilation is then considered as a case study. This practice, which involves (...) combining information from conventional observations and simulation-based forecasts, is characterized as a complex measuring practice that is still under development. The case study reveals challenges that are likely to resurface in other measuring practices that embed computer simulation. It is also noted that some practices that embed simulation are difficult to classify; they suggest a fuzzy boundary between measurement and non-measurement. 1 Introduction2 A Contemporary View of Measurement3 Three Types of Measurement4 Can Computer Simulations Measure Real-World Target Systems?5 Case Study: Atmospheric Data Assimilation5.1 Why data assimilation?5.2 A complex measuring practice under development5.3 Epistemic iteration6 The Boundaries of Measurement7 Epistemology, Not Terminology. (shrink)

Computer simulations and experiments share many important features. One way of explaining the similarities is to say that computer simulations just are experiments. This claim is quite popular in the literature. The aim of this paper is to argue against the claim and to develop an alternative explanation of why computer simulations resemble experiments. To this purpose, experiment is characterized in terms of an intervention on a system and of the observation of the reaction. Thus, if (...) class='Hi'>computer simulations are experiments, either the computer hardware or the target system must be intervened on and observed. I argue against the first option using the non-observation argument, among others. The second option is excluded by e.g. the over-control argument, which stresses epistemological differences between experiments and simulations. To account for the similarities between experiments and computer simulations, I propose to say that computer simulations can model possible experiments and do in fact often do so. (shrink)

Robertson's earlier work, The New Renaissance projected the likely future impact of computers in changing our culture. Phase Change builds on and deepens his assessment of the role of the computer as a tool driving profound change by examining the role of computers in changing the face of the sciences and mathematics. He shows that paradigm shifts in understanding in science have generally been triggered by the availability of new tools, allowing the investigator a new way of seeing into (...) questions that had not earlier been amenable to scientific probing. (shrink)

The subject of this study is the problem of the failure of attempts by the scientific community to come to a common understanding of what exactly information can be as something encoded into material structures and moved along with them. At the same time, the following aspects of this problem are considered in detail: what is the immediate cause of the information problem; what are the objective and subjective prerequisites for its appearance; why the unresolved nature of this problem does (...) not interfere with the creation and development of communication systems, control and other "smart" devices; is there any general guideline for finding solutions to such problems, and what is it; what role did the philosophy of information play in turning the problem of information from a private scientific problem into a problem of the ideological level. The main results of the conducted research are as follows: the immediate cause of the information problem has been identified and a comprehensively substantiated solution to this problem has been given; it has been revealed that the incompleteness of the materialistic theory of cognition has become a fertile ground for the appearance of this problem; the circumstances that prevented its completion have been identified; the natural mechanism of control and cognition has been revealed, as a result of which the materialistic theory of cognition has been further developed the source of the ideal in the material world is revealed; it is shown that the mechanistic idea of information coding made the concept of information incompatible with the presence of any objective content; it is revealed what is actually hidden behind the words about information coding and its measurement; the nature of signals and signs is revealed; a kind of bias of the philosophy of information and a general error is revealed all known concepts of information. (shrink)

What is computer-science about? CS is obviously the science of computers. But what exactly are computers? We know that there are physical computers, and, perhaps, also abstract computers. Let us limit the discussion here to physical entities and ask: What are physical computers? What does it mean for a physical entity to be a computer? The answer, it seems, is that physical computers are physical dynamical systems that implement formal entities such as Turing-machines. I do not think that (...) this answer is false. But it invites another, and troubling, question: What distinguishes computers from other physical dynamical systems? The difficulty is that, on the one hand, every physical system im-plements abstract formal entities such as sets of differential equations, while on the other hand we certainly do not want to count every dynamical system as a computer. After all, if CS is somehow distinctive, then there must be a difference between computers and other systems such as solar systems, stomachs, and carburetors. But what is the difference? (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)

Brain-Computer interfacing is a highly promising and fast developing field of modern life sciences. Recent advances in neuroscience together with progressing miniaturization in micro systems provide insights in structure and functioning of the human brain and enable connections of technical components to neuronal structures as well. This possibly offers a future therapy for paralysed patients through neuronal motor pros-theses. This paper identifies central ethical aspects which have to be considered in further progressing research in this scientific field and the (...) development of neuronal motor prostheses. (shrink)

Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.

What is computer art? Do the concepts we usually employ to talk about art, such as ‘meaning’, ‘form’ or ‘expression’ apply to computer art? _A Philosophy of Computer Art_ is the first book to explore these questions. Dominic Lopes argues that computer art challenges some of the basic tenets of traditional ways of thinking about and making art and that to understand computer art we need to place particular emphasis on terms such as ‘interactivity’ and (...) ‘user’. Drawing on a wealth of examples he also explains how the roles of the computer artist and computer art user distinguishes them from makers and spectators of traditional art forms and argues that computer art allows us to understand better the role of technology as an art medium. (shrink)

This study examined the effects of computer-assisted cognitive rehabilitation in a group of 16 brain-damaged patients. Therapeutic effectiveness was assessed by improvement on computer tasks, the results of neuropsychological tests and quality of life ratings. Participants suffered from mild to moderate attention and memory problems or aphasia. The procedure involved baseline assessment, a 15-week course of therapy conducted twice a week and posttest. Neuropsychological tests assessing attention, memory and language problems and quality of life ratings were administered twice: (...) in pre- and posttests. Twelve healthy controls were also examined twice using the same battery of neuropsychological tests. The RehaCom program and the Polish computer therapy program for aphasics called Afa-System were used for rehabilitation. The computer-assisted rehabilitation tasks were selected individually for each patient. The results showed significant improvement on computer-assisted tasks in all braindamaged subjects. However, none or very little improvement was observed on neuropsychological tests and quality of life ratings. The results of the study confirm the importance of using different types of measures to estimate the effectiveness of computer-assisted neuropsychological rehabilitation as well as the necessity of applying various kinds of therapy to improve cognitive, emotional and social functioning in brain-damaged patients. (shrink)

In this article, I develop three conceptual innovations within the area of formal metatheory, and present a computer program, called Reconstructor, that implements those developments. The first development consists in a methodology for testing formal reconstructions of scientific theories, which involves checking both whether translations of paradigmatically successful applications into models satisfy the formalisation of the laws, and also whether unsuccessful applications do not. I show how Reconstructor can help carry this out, since it allows the end-user to specify (...) a formal language, input axioms and models formulated in that language, and then ask if the models satisfy the axioms. The second innovation is the introduction of incomplete models (for which the denotation of some terms is missing) into scientific metatheory, in order to represent cases of missing information. I specify the paracomplete semantics built into Reconstructor to deal with sentences where denotation failures occur. The third development consists in a new way of explicating the structuralist notion of a determination method, by equating them with algorithms. This allows determination methods to be loaded into Reconstructor and then executed within a model to find out the value of a previously non-denoting term (i.e. it allows the formal reconstruction to make predictions). This, in turn, can help test the reconstruction in a different way. Finally, I conclude with some suggestions about additional uses the program may have. (shrink)

It's uncontroversial that notions of idealization and approximation are central to understanding computer simulations and their rationale. What's not so clear is what exactly these notions come to. Two distinct forms of approximation will be distinguished and their features contrasted with those of idealizations. These distinctions will be refined and closely tied to computer simulations by means of Scott-Strachey denotational programming semantics. The use of this sort of semantics also provides a convenient format for argumentation in favor of (...) several theses I shall propose concerning the role computer implemented approximations and idealizations play in fixing what the acceptance of an underlying scientific theory is or should be. (shrink)

Defenders of educational frog dissection tend to emphasize the claim that computer-simulated alternatives cannot replicate the same exact experience of slicing open a frog, with all its queasy and visceral impact. Without denying that point, I argue that this is not the only educational standard against which computer-simulated dissection should be evaluated. When real-world frog dissection is analyzed as a concrete technological practice rather than an assumed ideal, the particular educational advantages distinct to real-world dissection and virtual dissection (...) can be enumerated and compared. Building on the work of John Dewey and Don Ihde, I explore the still-expanding advantages of computer-simulated dissection, and in this proper context of comparison it becomes clear that virtual alternatives are increasingly the more educationally beneficial option. (shrink)

Computer simulations are widely used in current scientific practice, as a tool to obtain information about various phenomena. Scientists accordingly rely on the outputs of computer simulations to make statements about the empirical world. In that sense, simulations seem to enable scientists to acquire empirical knowledge. The aim of this paper is to assess whether computer simulations actually allow for the production of empirical knowledge, and how. It provides an epistemological analysis of present-day empirical science, to which (...) the traditional epistemological categories cannot apply in any simple way. Our strategy consists in acknowledging the complexity of scientific practice, and trying to assess its rationality. Hence, while we are careful not to abstract away from the details of scientific practice, our approach is not strictly descriptive: our goal is to state in what conditions empirical science can rely on computer simulations. In order to do so, we need to adopt a renewed epistemological framework, whose categories would enable us to give a finer-grained, and better-fitted analysis of the rationality of scientific practice. (shrink)

Brain–computer interfacing (BCI) aims at directly capturing brain activity in order to enable a user to drive an application such as a wheelchair without using peripheral neural or motor systems. Low signal to noise ratio’s, low processing speed, and huge intra- and inter-subject variability currently call for the addition of intelligence to the applications, in order to compensate for errors in the production and/or the decoding of brain signals. However, the combination of minds and machines through BCI’s and intelligent (...) devices (IDs) can affect a user’s sense of agency. Particularly confusing cases can arise when the behavioral control switches implicitly from user to ID. I will suggest that in such situations users may be insecure about the extent to which the resulting behavior, whether successful or unsuccessful, is genuinely their own. Hence, while performing an action, a user of a BCI–ID may be uncertain about being the agent of the act. Several cases will be examined and some implications for (legal) responsibility (e.g. establishing the presence of a ‘guilty mind’) are discussed. (shrink)

278 non-freshman university students taking a l2-week critical thinking course in a large single-section class, with computer-assisted guided practice as a replacement for small-group discussion, and all testing in machine-scored multiple-choice format, improved their critical thinking skills, as measured by the California Critical Thinking Skills Test, by half a standard deviation, a moderate improvement. The improvement was more than that reported with a traditional format without computer-assisted instruction, but less than that reported with a format using both (...) class='Hi'>computer-assisted instruction and essay-type assignments. Further studies are needed to test hypotheses suggested by these results. (shrink)

Reasons are given to justify the claim that computer simulations and computational science constitute a distinctively new set of scientific methods and that these methods introduce new issues in the philosophy of science. These issues are both epistemological and methodological in kind.