The development of technology is unbelievably rapid. From limited local networks to high speed Internet, from crude computing machines to powerful semi-conductors, the world had changed drastically compared to just a few decades ago. In the constantly renewing process of adapting to such an unnaturally high-entropy setting, innovations as well as entirely new concepts, were often born. In the business world, one such phenomenon was the creation of a new type of entrepreneurship. This paper proposes a new academic discipline of (...) computational entrepreneurship, which centers on: (i) an exponentially growing (and less expensive) computing power, to the extent that almost everybody in a modern society can own and use that; (ii) omnipresent high-speed Internet connectivity, wired or wireless, representing our modern day’s economic connectomics; (iii) growing concern of exploiting “serendipity” for a strategic commercial advantage; and (iv) growing capabilities of lay people in performing calculations for their informed decisions in taking fast-moving entrepreneurial opportunities. Computational entrepreneurship has slowly become a new mode of operation for business ventures and will likely bring the academic discipline of entrepreneurship back to mainstream economics. (shrink)

A small consortium of philosophers has begun work on the implications of epistemic networks (Zollman 2008 and forthcoming; Grim 2006, 2007; Weisberg and Muldoon forthcoming), building on theoretical work in economics, computer science, and engineering (Bala and Goyal 1998, Kleinberg 2001; Amaral et. al., 2004) and on some experimental work in social psychology (Mason, Jones, and Goldstone, 2008). This paper outlines core philosophical results and extends those results to the specific question of thresholds. Epistemic maximization of certain types does (...) show clear threshold effects. Intriguingly, however, those effects appear to be importantly independent from more familiar threshold effects in networks. (shrink)

In the field of applied computer research, the problem of the reinforcement of existing inequalities through the processing of “big data” in neural networks is typically addressed via concepts of representation and fairness. These approaches, however, tend to overlook the limits of the liberal antidiscrimination discourse, which are well established in critical theory. In this paper, I address these limits and propose a different framework for understanding technologically amplified oppression departing from the notion of “mute compulsion” (Marx), a specifically (...) modern form of power based on the social abstraction of wage labor in market exchange. I begin with a reconstruction of the process of technological abstraction in automated pattern recognition, after which I summarize the conceptional shortcomings of representational fairness discourse. In contrast, I demonstrate how the social reproduction of exploitation is conceptualized in critical theory as being mediated through a process of social abstraction, defined as a social practice of reification that manifest in fetishization. To avoid economistic shortcomings, I contextualize the argument of social abstraction against the backdrop of social reproduction theory, which takes the juncture of various historical forms of oppression into account. I conclude by elaborating how technological abstraction corresponds to the problem of mute compulsion by replicating processes of social abstraction. (shrink)

This research aims to clarify, by constructing and testing a computer simulation, the use of multiple representations in problem solving, focusing on their role in visual reasoning. The model is motivated by extensive experimental evidence in the literature for the features it incorporates, but this article focuses on the system's structure. We illustrate the model's behavior by simulating the cognitive and perceptual processes of an economics expert as he teaches some well‐learned economics principles while drawing a graph on a (...) blackboard. Data in the experimental literature and concurrent verbal protocols were used to guide construction of a linked production system and parallel network, CaMeRa (Computation with Multiple Representations), that employs a “Mind's Eye” representation for pictorial information, consisting of a bitmap and associated node‐link structures. Propositional list structures are used to represent verbal information and reasoning. Small individual pieces from the different representations are linked on a sequential and temporary basis to form a reasoning and inferencing chain, using visually encoded information recalled to the Mind's Eye from long‐term memory and from cues recognized on an external display. CaMeRa, like the expert, uses the diagrammatic and verbal representations to complement one another, thus exploiting the unique advantages of each. (shrink)

The aim of this dissertation is to clarify the debate over the explanation of quantum speedup and to submit, for the reader's consideration, a tentative resolution to it. In particular, I argue, in this dissertation, that the physical explanation for quantum speedup is precisely the fact that the phenomenon of quantum entanglement enables a quantum computer to fully exploit the representational capacity of Hilbert space. This is impossible for classical systems, joint states of which must always be representable as (...) product states. I begin the dissertation by considering, in Chapter 2, the most popular of the candidate physical explanations for quantum speedup: the many worlds explanation of quantum computation. I argue that, although it is inspired by the neo-Everettian interpretation of quantum mechanics, unlike the latter it does not have the conceptual resources required to overcome objections such as the so-called `preferred basis objection'. I further argue that the many worlds explanation, at best, can serve as a good description of the physical process which takes place in so-called network-based computation, but that it is incompatible with other models of computation such as cluster state quantum computing. I next consider, in Chapter 3, a common component of most other candidate explanations of quantum speedup: quantum entanglement. I investigate whether entanglement can be said to be a necessary component of any explanation for quantum speedup, and I consider two major purported counter-examples to this claim. I argue that neither of these, in fact, show that entanglement is unnecessary for speedup, and that, on the contrary, we should conclude that it is. In Chapters 4 and 5 I then ask whether entanglement can be said to be sufficient as well. In Chapter 4 I argue that despite a result that seems to indicate the contrary, entanglement, considered as a resource, can be seen as sufficient to enable quantum speedup. Finally, in Chapter 5 I argue that entanglement is sufficient to explain quantum speedup as well. (shrink)

A great deal of attention has been paid in recent years to the legality of the actions of states and state agents in international and non-international cyber conflicts. Less attention has been paid to ethical considerations in these situations, and very little has been written regarding the ethics of the participation of non-state actors in such conflicts. In this article, I analyze different categories of non-state participation in cyber operations and undertake to show under what conditions such actions, though illegal, (...) might be morally defensible. (shrink)

E-games are a dramatically expanding dimension of contemporary exploitations of computing and computer network technologies - one that, thus far, has evoked much more heat among parents and politicians than light in the form of serious scholarly and philosophical analysis. We argue that e-games deserve such analysis in part because of their intrinsic philosophical interest as they raise primary philosophical questions of ontology, epistemology, human nature, the character of "gameplay," - and most especially, of ethics. We further suggest (...) that such analyses - exemplified by the articles collected here - may also contribute to resolving the larger social and political debates evoked by e-games. (shrink)

The application of machine learning touches all activities of human behavior such as computer network and routing packets in LAN. In the field of our research here, emphasis was placed on extracting weights that would affect the speed of the network's response and finding the best path, such as the number of nodes in the path and the congestion on each path, in addition to the cache used for each node. Therefore, the use of these elements in (...) building the neural network is worthy, as is the exploitation of the feed forwarding and the backpropagation in the neural network in order to reach the best prediction for the best path. The goal of the proposed neural network is to minimize the network time delay within the optimization of the packet paths being addressed in this study. The shortest path is considered as the key issue in routing algorithm that can be carried out with real time of path computations. Exploiting the gaps in previous studies, which are represented in the lack of training of the system and the inaccurate prediction as a result of not taking into consideration the hidden layers' feedback, leads to great performance. This study aims to suggest an efficient algorithm that could help in selecting the shortest path to improve the existing methods using weights derived from packet ID and to change neural network iteration simultaneously. In this study, the design of the efficient neural network of appropriate output is discussed in detail including the principles of the network. The findings of the study revealed that exploiting the power of computational system to demonstrate computer simulation is really effective. It is also shown that the system achieved good results when training the neural network system to get 2.4% time delay with 5 nodes in local LAN. Besides, the results showed that the major features of the proposed model will be able to run in real time and are also adaptive to change with path topology. (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)

How do people use information from others to solve complex problems? Prior work has addressed this question by placing people in social learning situations where the problems they were asked to solve required varying degrees of exploration. This past work uncovered important interactions between groups' connectivity and the problem's complexity: the advantage of less connected networks over more connected networks increased as exploration was increasingly required for optimally solving the problem at hand. We propose the Social Interpolation Model (SIM), an (...) agent‐based model to explore the cognitive mechanisms that can underlie exploratory behavior in groups. Through results from simulation experiments, we conclude that “exploration” may not be a single cognitive property, but rather the emergent result of three distinct behavioral and cognitive mechanisms, namely, (a) breadth of generalization, (b) quality of prior expectation, and (c) relative valuation of self‐obtained information. We formalize these mechanisms in the SIM, and explore their effects on group dynamics and success at solving different kinds of problems. Our main finding is that broad generalization and high quality of prior expectation facilitate successful search in environments where exploration is important, and hinder successful search in environments where exploitation alone is sufficient. (shrink)

Computer vision is one of AI’s most successful fields. In the last twenty years, machines have become increasingly good at extracting information from images and at identifying objects. But does this mean that machines really can see, or is computer vision just a fancy metaphor for object detection? This paper aims to provide a reasoned answer to the question. First, three criteria for vision attribution are reviewed and it is argued that a functionalist criterion, in terms of exploitable (...) internal representations based on visual stimuli, fares better than behaviourist or phenomenological ones. The functionalist criterion is then applied to vision algorithms based on neural networks and it is argued that such machines can indeed see, insofar as neural networks are precisely trained to generate representations of the visual data they are fed with. Those representations present the specific traits associated with successful training: They are hierarchical, robust, and versatile. We argue that these properties may be used as further constraints on representational devices in general, helping to solve some of the classical issues faced by teleosemantic theories of representation such as that expounded by Dretske. (shrink)

Network theory is necessary for the realization of cognitive representations and resulting empirical observations of social groups. We propose that the triadic primitives denoting individual roles are multilayer, with positive and negative relations feeding into cost–benefit calculations. Through this, we advance a computational theory that generalizes to different scales and to contexts where conflict is not present.

A simple recurrent artificial neural network is used to classify situations as permissible or impermissible. The trained ANN can be understood as having set up a similarity space of cases at the level of its internal or hidden units. An analysis of the network’s internal representations is undertaken using a new visualization technique for state space approaches to understanding similarity. Insights from the literature on moral philosophy pertaining to contributory standards will be used to interpret the state space (...) set up by the ANN as being structured by implicit reasons. The ANN, on its own, is not capable of explicitly representing or offering reasons to itself or others. That said, the low level similarity space set up by the network could be made available to higher order processes that exploit it for case-based reasoning. It is argued that for normative purposes, similarity could be seen as a contributor to procedural coherence in case-based reasoning and local forms of substantive coherence, but not to global forms of coherence given the computational complexity of managing those more ambitious forms of coherence. (shrink)

Probabilistic Relational Models (PRMs) are a framework for compactly representing uncertainties (actually probabilities). They result from the combination of Bayesian Networks (BNs), Object-Oriented languages, and relational models. They are specifically designed for their efficient construction, maintenance and exploitation for very large scale problems, where BNs are known to perform poorly. Actually, in large-scale problems, it is often the case that BNs result from the combination of patterns (small BN fragments) repeated many times. PRMs exploit this feature by defining these (...) patterns only once (the so-called PRM’s classes) and using them through multiple instances, as prescribed by the Object-Oriented paradigm. This design induces low construction and maintenance costs. In addition, by exploiting the classes’ structures, PRM’s state-of-the-art inference algorithm “Structured Variable Elimination” (SVE) significantly outperforms BN’s classical inference algorithms (e.g., Variable Elimination, VE; Local Conditioning, LC). SVE is actually an extension of VE that simply exploits classes to avoid redundant computations. In this article, we show that SVE can be enhanced using LC. Although LC is often thought as being outperformed by VE-like algorithms in BNs, we do think that it should play an important role for PRMs because its features are very well suited for best exploiting PRM classes. In this article, relying on Faÿ and Jaffray’s works, we show how LC can be used in conjunction with VE and deduce an extension of SVE that outperforms it for large-scale problems. Numerical experiments highlight the practical efficiency of our algorithm. (shrink)

To maximize brain plasticity after stroke, several rehabilitation strategies have been explored, including the use of intensive motor training, motor imagery, and action observation. Growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has been shown. However, most VR tools are designed to exploit active movement, and hence patients with low level of motor control cannot fully benefit from them. Consequently, the idea of directly training the central nervous system has been promoted by utilizing (...) motor-imagery (MI) based brain-computer interfaces (BCIs). To date, detailed information on which VR strategies lead to successful functional recovery is still largely missing, and very little is known about how to optimally integrate BCI and VR paradigms for stroke rehabilitation. The purpose of this study was to examine the efficacy of a BCI-VR system using a MI paradigm for post-stroke upper limb rehabilitation on functional assessments, and related changes in MI ability and brain imaging. To achieve this, a 60 years old male chronic stroke patient was recruited. The patient underwent a 3-week intervention in a clinical environment, resulting in 10 BCI-VR training sessions. The patient was assessed before and after intervention, as well as on a one-month follow-up, in terms of clinical scales and brain imaging using functional MRI (fMRI). Consistent with prior research, we found important improvements in upper extremity scores (Fugl-Meyer) and identified increases in brain activation measured by fMRI that suggest neuroplastic changes in brain motor networks. This study expands on the current body of evidence as more data are needed on the effect of this type of interventions not only on functional improvement but also through brain imaging to study the effect of the intervention on plasticity. (shrink)

This aricle discusses the similarity between the propagation of pathogens (viruses and worms) on computer networks and the proliferation of pathogens in cellular organisms (organisms with genetic material contained within a membrane-encased nucleus). It introduces several biological mechanisms which are used in these organisms to protect against such pathogens and presents security models for networked computers inspired by several biological paradigms, including genomics (RNA interference), proteomics (pathway mapping), and physiology (immune system). In addition, the study of epidemiological models for (...) disease control can inspire methods for controlling the spread of pathogens across multiple nodes of a network. It also presents results based on the authors’ research in immune system modeling. (shrink)

An earlier version of this paper was presented at the 2011 IEEE International Symposium on Technology and Society at Saint Xavier University in Chicago, Illinois. The focus of this paper is to present observations related to information assurance in rural and urban populations. Based on our experience teaching college students in these environments, we have noted that on entering school, generally, individuals demonstrate limited background knowledge of a variety of computer related technologies. Students begin with a technical disadvantage that (...) represents a readily exploitable attack vector for identity thieves. Because of the experience deficit, the hazard of identity theft is significant with possible severe detrimental outcomes for the student victim. In addition, the negative impact on the society as a whole is substantial. Methods that reach beyond traditional formal computer or network security instruction in the classroom and extend information assurance education across disciplines are needed. We have explored this direction at the university and have worked on strategies to educate students about identity theft. The interdisciplinary programs outlined here span the curriculum. In addition, we suggest community outreach programs that extend the scope of influence of information assurance education beyond the university to include surrounding at risk populations. (shrink)

This book deals with the major ethical and social implications of computer networking and its technological development. In this book, a number of leading thinkers--philosophers, computer scientists and researchers--address some fundamental questions posed by the new technology.

The tenuous network of interconnected data that supports our nation's critical infrastructure has been built up, computer by computer, over only the last few decades. From punch cards to the supercomputers constructed by pioneers in today's fields, computers have been controlling our nation's critical sectors nearly every step of the way. As designers of today's critical systems gravitate slowly towards systems that require less human oversight than ever before, the vulnerability of the networks that control our electricity (...) systems, water supply, and banking services also continues to increase. In recent control system security reviews, the Departments of Energy and Homeland Security hired experts from Idaho National Labs who found that not only do "all of the evaluated systems suffer from high-impact security vulnerabilities that could be exploited by a low-skill-level attacker," but "in currently deployed systems, enhanced security controls cannot easily be implemented while still assuring basic system functionality". While the federal government has attempted on several occasions to outline its strategy to implement cybersecurity policies, its defining statement on the issue is in the form of the National Infrastructure Protection Plan. Even then, these government documents mean little if neither government nor private agencies implement them in their respective fields. (shrink)

In Belnap's useful 4-valued logic, the set 2 = {T, F} of classical truth values is generalized to the set 4 = ������(2) = {Ø, {T}, {F}, {T, F}}. In the present paper, we argue in favor of extending this process to the set 16 = ᵍ (4) (and beyond). It turns out that this generalization is well-motivated and leads from the bilattice FOUR₂ with an information and a truth-and-falsity ordering to another algebraic structure, namely the trilattice SIXTEEN₃ with an (...) information ordering together with a truth ordering and a (distinct) falsity ordering. Interestingly, the logics generated separately by the algebraic operations under the truth order and under the falsity order in SIXTEEN₃ coincide with the logic of FOUR₂, namely first degree entailment. This observation may be taken as a further indication of the significance of first degree entailment. In the present setting, however, it becomes rather natural to consider also logical systems in the language obtained by combining the vocabulary of the logic of the truth order and the falsity order. We semantically define the logics of the two orderings in the extended language and in both cases axiomatize a certain fragment comprising three unary operations: a negation, an involution, and their combination. We also suggest two other definitions of logics in the full language, including a bi-consequence system. In other words, in addition to presenting first degree entailment as a useful 16-valued logic, we define further useful 16-valued logics for reasoning about truth and (non-)falsity. We expect these logics to be an interesting and useful instrument in information processing, especially when we deal with a net of hierarchically interconnected computers. We also briefly discuss Arieli's and Avron's notion of a logical bilattice and state a number of open problems for future research. (shrink)

The critical node detection problem is a central task in computational graph theory due to its large applicability, consisting in deleting $k$ nodes to minimize a certain graph measure. In this article, we propose a new Extremal Optimization-based approach, the Pseudo-Deterministic Noisy Extremal Optimization (PDNEO) algorithm, to solve the Critical Node Detection variant in which the pairwise connectivity is minimized. PDNEO uses an adaptive pseudo-deterministic parameter to switch between random nodes and articulation points during the search, as well as other (...) features, such as noise induction to preserve diversity, greedy search to better exploit the search space and a greater search space exploration mechanism. Numerical experiments on synthetic and real-world networks show the effectiveness of the proposed algorithm compared with existing methods. (shrink)

There is much effort nowadays to protect communication networks against different cybersecurity attacks (which are more and more sophisticated) that look for systems’ vulnerabilities they could exploit for malicious purposes. Network Intrusion Detection Systems (NIDSs) are popular tools to detect and classify such attacks, most of them based on ML models. However, ML-based NIDSs cannot be trained by feeding them with network traffic data as it is. Thus, a Feature Engineering (FE) process plays a crucial role transforming (...) class='Hi'>network traffic raw data onto derived one suitable for ML models. In this work, we study the effects of applying one such FE technique in different ways on the performance of two ML models (linear and non-linear) and their selected features. This the Feature as a Counter approach. The derived observations are computed from either with the same number of raw samples, (batch-based approaches) or by aggregating them by time intervals (timestamp-based approach). Results show that there is no significant differences between the proposed approaches neither in the performance of the models nor in the selected features that validate our proposal making it feasible to be widely used as a standard FE method. (shrink)

The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individuals. Drawing on Sen and Nussbaum’s capability approach, we present a framework formalizing a network of ethical concepts and entitlements necessary for AI systems to confer meaningful benefit or assistance to stakeholders. Such systems enhance stakeholders’ ability to advance their life plans and well-being while upholding their fundamental rights. We characterize two necessary conditions for (...) morally permissible interactions between AI systems and those impacted by their functioning, and two sufficient conditions for realizing the ideal of meaningful benefit. We then contrast this ideal with several salient failure modes, namely, forms of social interactions that constitute unjustified paternalism, coercion, deception, exploitation and domination. The proliferation of incidents involving AI in high-stakes domains underscores the gravity of these issues and the imperative to take an ethics-led approach to AI systems from their inception. (shrink)

The first decade of the twenty-first century introduced a cultural shift where terrorism is concerned by making new technologies such as computers and networks available as both tools and targets for exploitation. The current rise in the number of attempts at launching a cyber attack may represent a new generation of “terrorists” and their discontent with governments, private companies, or with other non-governmental groups. Using cyber technologies has many benefits for the user and the potential of causing more damage (...) by a keystroke than a bomb is increasing daily. Despite much recent scholarship on cyber terrorism, however, there continue to be problems not only in defining what cyber terrorism means but in identifying both who are the actors and the panoply of choices actors confront. In this essay, I attempt to clarify these problems by defining key terms and by analyzing the recent escalation in cyber use in the European context. (shrink)

This Neurocomputing special issue is based on selected, expanded and significantly revised versions of papers presented at the Second International Conference on Brain Inspired Cognitive Systems (BICS 2006) held at Lesvos, Greece, from 10 to 14 October 2006. The aim of BICS 2006, which followed the very successful first BICS 2004 held at Stirling, Scotland, was to bring together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, (...) specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. The biennial BICS Conference Series (with BICS 2008 recently held in Sao Luis, Brazil, 24–27 June, and BICS 2010 due to be held in Madrid, Spain) aims to become a major point of contact for research scientists, engineers and practitioners throughout the world in the fields of cognitive and computational systems inspired by the brain and biology. The first paper in this special issue is by Carnell who presents an analysis of the use of Hebbian and Anti-Hebbian spike timedependent plasticity (STDP) learning functions within the context of recurrent spiking neural networks. He shows that under specific conditions Hebbian and Anti-Hebbian learning can be considered approximately equivalent. Finally, the author demonstrates that such a network habituates to a given stimulus and is capable of detecting subtle variations in the structure of the stimuli itself. Hodge, O’Keefe and Austin present a binary neural shape matcher using Johnson counters and chain codes. They show that images may be matched as whole images or using shape matching. Finally, they demonstrate shape matching using a binary associative-memory neural network to index and match chain codes where the chain code elements are represented by Johnson codes. (shrink)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even (...) if you do not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)

Fluid neural networks can be used as a theoretical framework for a wide range of complex systems as social insects. In this article we show that collective logical gates can be built in such a way that complex computation can be possible by means of the interplay between local interactions and the collective creation of a global field. This is exemplified by a NOR gate. Some general implications for ant societies are outlined. ©.

According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an (...) ambiguous context. To determine meanings of constructions starting from ambiguous contexts, we rely on the principle of cross‐situational learning. While this mechanism has been implemented in several computational models, these models typically focus on learning mappings between words and referents. In contrast, in our model, we show how cross‐situational learning can be applied consistently to learn correspondences between form and meaning beyond such simple correspondences. (shrink)

Imagine this scenario: a bank customer walks up to an ATM to withdraw cash from her account. While entering her PIN, she accidentally presses the '3' key at the same time as the 'Clear' key. Instantly $100 comes out of the cash dispenser! Curious, she checks the receipt and seeing that the money did not from her account, she tries the same operation. Again, $100 comes out of the cash dispenser. At this point she has two options, A: she can (...) continue to take advantage of this obvious flaw and tell her friends, or B: she can report this problem to the bank, telling no one else. While Kantian ethics might require the latter, the issue becomes much grayer when it comes to computer software vulnerabilities. Many variables exist to cloud the ethical judgment of a software flaw's discoverer. The question becomes: is it better to report any vulnerability that could cause catastrophic problems or to make the vulnerability information public in order to simultaneously compel the software vendor to address the problem while giving the vendor's customers a chance to prepare for potential exploitation? Software companies are facing this dilemma on a regular basis. There are dozens of websites, newsgroups, and e-mail lists dedicated to the task of sharing vulnerability information, whether condoned by the software company or not. The issue increases in severity as vulnerable software becomes ubiquitous across global networks. The public release of vulnerability information is often the first drop of the monsoon that is the malicious network worm. How this information is controlled and disseminated is critical to the stable operation of millions of computer systems and networks across the globe.Modern software with network capability is fundamentally complex and can span thousands of lines of source code for one small part of the package. Without proper testing and quality assurance, many bugs and errors slip through. Software development requires these iterations of coding and bug fixing to produce stable and polished final products. Larger and more complex software gives a greater chance for a bug to remain undiscovered. Yet, since major vulnerabilities have appeared in relatively smaller projects, proper code audit and testing are critical regardless of the size of a software package or the amount of source code required to produce it. If bugs or security vulnerabilities are not discovered and fixed by the software manufacturers, it is inevitable that they will be discovered by outside researchers.This breeds the ethical conundrum of what the researchers do with the information once it has been discovered. Foundational to disclosure, regardless of the ideology, is the notion of providing useful protective information to the most appropriate audience. Many suggest that disclosure is about doing the 'greatest good' for the greatest number of people, which is an obvious adherence to the ethical principle of Utilitarianism. There are numerous parties involved in the network security process such as software vendor, security researcher, system administrator, and even malicious attacker: all whose intentions reflect on the ethical principles behind their actions. (shrink)

We study human performance in two classical NP‐hard optimization problems: Set Cover and Maximum Coverage. We suggest that Set Cover and Max Coverage are related to means selection problems that arise in human problem‐solving and in pursuing multiple goals: The relationship between goals and means is expressed as a bipartite graph where edges between means and goals indicate which means can be used to achieve which goals. While these problems are believed to be computationally intractable in general, they become more (...) tractable when the structure of the network resembles a tree. Thus, our main prediction is that people should perform better with goal systems that are more tree‐like. We report three behavioral experiments which confirm this prediction. Our results suggest that combinatorial parameters that are instrumental to algorithm design can also be useful for understanding when and why people struggle to choose between multiple means to achieve multiple goals. (shrink)

I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well fall into this last class.

In this wide-ranging conversation, Berry and Galloway explore the implications of undertaking media theoretical work for critiquing the digital in a time when networks proliferate and, as Galloway claims, we need to ‘forget Deleuze’. Through the lens of Galloway’s new book, Laruelle: Against the Digital, the potential of a ‘non-philosophy’ for media is probed. From the import of the allegorical method from excommunication to the question of networks, they discuss Galloway’s recent work and reflect on the implications of computation for (...) media theory, thinking about media objects, and critical theory. (shrink)

The book is an epistemological monograph written from a multidisciplinary perspective. It provides a complex and realistic picture of cognition and rationality, as endowments aimed at making sense and reacting smartly to one's environment, be it epistemic, social or simply ecological. The first part of the book analyzes scientific modeling as products of the biological necessity to cope with the environment and be able to draw as many inferences as possible about it. Moreover, it develops an epistemological framework which will (...) be exploited in both the second part of the book, focusing on social cognition and cognitive niche construction, and the third part, dealing with the apparent irrationality of magical and religious belief. The book also discusses how both social networking and online religion influence cognition, rationality and irrational belief. (shrink)

Various threshold Boolean networks, a formalism used to model different types of biological networks, can produce similar dynamics, i.e. share same behaviors. Among them, some are complex, others not. By computing both structural and behavioral complexities, we show that most TBNs are structurally complex, even those having simple behaviors. For this purpose, we developed a new method to compute the structural complexity of a TBN based on estimates of the sizes of equivalence classes of the threshold Boolean functions composing the (...) TBN. (shrink)

Education ecology is a new crossover research field in network age. Its research content can be either microscopic classroom teaching or macro educational ecology research on teaching and culture. The university music classroom is a special kind of ecology. The reason why this is special is that compared to natural ecology, the classroom ecology of university music has a unique relationship between the environment and the subject. The classroom is ecological and becomes the logical prerequisite for ecological research in (...) the classroom. In the Internet age, as the most advanced teaching medium, it has become the need for the development of the new era. The Internet era has broadened the channels and scope of people's access to information and greatly enriched the information resources. The design of teacher's music teaching should have sustainable development. It is no longer a pursuit of only the answer. It must consider the students' multiple ways of learning and must leave room for students to practice independently. Guides help students continue to explore musical arts. This article mainly conveys the innovation of the traditional teaching “learning” and “learning” dichotomy to form an interactive and harmonious classroom ecosystem. The interaction between various factors has handled according to the principles of educational ecology, combined with the development of network technology and Cultivate students' enthusiasm for learning, self-study ability and practical ability, to improve the effectiveness of university music teaching. (shrink)

The title of this book was inspired by a passage in Charles Sherrington's Man on his Nature.

The past three decades of policy process studies have seen the emergence of a clear intellectual lineage with regard to complexity. Implicitly or explicitly, scholars have employed complexity theory to examine the intricate dynamics of collective action in political contexts. However, the methodological counterparts to complexity theory, such as computational methods, are rarely used and, even if they are, they are often detached from established policy process theory. Building on a critical review of the application of complexity theory to policy (...) process studies, we present and implement a baseline model of policy processes using the logic of coevolving networks. Our model suggests that an actor’s influence depends on their environment and on exogenous events facilitating dialogue and consensus-building. Our results validate previous opinion dynamics models and generate novel patterns. Our discussion provides ground for further research and outlines the path for the field to achieve a computational turn. (shrink)

This text presents the research field of natural/unconventional computing as it appears in the book COMPUTING NATURE. The articles discussed consist a selection of works from the Symposium on Natural Computing at AISB-IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. The COMPUTING NATURE is about nature considered as the totality of physical existence, the universe. (...) By physical we mean all phenomena, objects and processes, that are possible to detect either directly by our senses or via instruments. Historically, there have been many ways of describing the universe (cosmic egg, cosmic tree, theistic universe, mechanistic universe) while a particularly prominent contemporary approach is computational universe, as discussed in this article. See more: http://arxiv.org/abs/1210.7784. (shrink)

The power of some new entrants to the music industry derives from their position as brokers in computer-mediated environments. Brokers act instrumentally to exploit their position within a network which, in turn, depends on their ability to build and sustain links (and, in computer-mediated environments, hyperlinks). Bricolage in computer-mediated entrepreneurship refers to the intuitive manipulation of resources in order to achieve (perhaps tacit) goals. Without careful stewardship of the new intellectual wealth thus created, bricolage may profit (...) neither the individual nor the wider community. (shrink)

In a seminal 1977 article, Rumelhart argued that perception required the simultaneous use of multiple sources of information, allowing perceivers to optimally interpret sensory information at many levels of representation in real time as information arrives. Building on Rumelhart's arguments, we present the Interactive Activation hypothesis—the idea that the mechanism used in perception and comprehension to achieve these feats exploits an interactive activation process implemented through the bidirectional propagation of activation among simple processing units. We then examine the interactive activation (...) model of letter and word perception and the TRACE model of speech perception, as early attempts to explore this hypothesis, and review the experimental evidence relevant to their assumptions and predictions. We consider how well these models address the computational challenge posed by the problem of perception, and we consider how consistent they are with evidence from behavioral experiments. We examine empirical and theoretical controversies surrounding the idea of interactive processing, including a controversy that swirls around the relationship between interactive computation and optimal Bayesian inference. Some of the implementation details of early versions of interactive activation models caused deviation from optimality and from aspects of human performance data. More recent versions of these models, however, overcome these deficiencies. Among these is a model called the multinomial interactive activation model, which explicitly links interactive activation and Bayesian computations. We also review evidence from neurophysiological and neuroimaging studies supporting the view that interactive processing is a characteristic of the perceptual processing machinery in the brain. In sum, we argue that a computational analysis, as well as behavioral and neuroscience evidence, all support the Interactive Activation hypothesis. The evidence suggests that contemporary versions of models based on the idea of interactive activation continue to provide a basis for efforts to achieve a fuller understanding of the process of perception. (shrink)

The connected and acyclic components contained in a network are identified by the computation of its complexity, where complexity of a network refers to the total number of spanning trees present within. The article in hand deals with the enumeration of the complexity of various networks’ operations such as sum, product, difference K 2, n ⊖ K 2, and the conjunction of S n with K 2. All our computations have been concluded by implementation of the methods of (...) linear algebra and matrix theory. Our derivations will also be highlighted with the assistance of 3D plots at the end of this article. (shrink)