Drawing on face-to-face and online ethnographic, survey and interview data with participants in distributed computing projects around the world, this book sheds light on the organizational and social structures of voluntary distributed computing projects, communities and teams, with close attention to questions of motivation in projects that offer little or no traditional forms of reward, either financially or in terms of participants' careers. With its focus on non-market, non-hierarchical cooperation, this book is a case study of (...) networked individuals around the world who are part of a new social production of information. (shrink)

Two analyzes of Spark engine performance strategies to implement the Spark technique in a matrix distributed computational algorithm, the multiplication of a sparse multiplication operational test model. The dimensions of the two input sparse matrices have been fixed to 30,000 × 30,000, and the density of the input matrix have been changed. The experimental results show that when the density reaches about 0.3, the original dense matrix multiplication performance can outperform the sparse-sparse matrix multiplication, which is basically consistent with (...) the relationship between the sparse matrix multiplication implementation in the single-machine sparse matrix test and the computational performance of the local native library. When the density of the fixed sparse matrix is 0.01, the distributed density-sparse matrix multiplication outperforms the same sparsity but uses the density matrix storage, and the acceleration ratio increases from 1.88× to 5.71× with the increase in dimension. The overall performance of distributed operations is improved. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 550-573, July 2022.

In the early years of the 1990s, a number of philosophers and cognitive scientists became enthused about the idea that mental states are spatially and temporally distributed in the brain, and that this has significant consequences for philosophy of mind. Daniel Dennett (1991), for example, appealed to the spatial and temporal distribution of cognitive processes in the brain in order to argue that there is no unified place where or time when consciousness occurs in the brain. Dennett used this (...) interim conclusion as a premise in a series of arguments designed to undermine what he calls the “Cartesian Theater” view of consciousness, according to which there is an independent and fact of the matter about when and where conscious mental states occur. Most famously, Dennett argues that anyone who believes there are such facts of the matter must choose between “Orwellian” and “Stalinesque” theories of the timing of consciousness, in order to accommodate certain data about the spatial distribution of the timing of consciousness-related brain events. But, he claims, that distinction is a distinction without a difference: The choice between “Orwellian” and “Stalinesque” views is either nonsense, or at the very least one that we could never be justified in making. And this, Dennett takes it, is a reductio ad absurdum of any theory of consciousness that says there is a fact of the matter about when and where is occurs. (shrink)

This paper presents ongoing research towards understanding the discourse and workspace in computer-mediated interactions. We present a series of methods developed to study non-collocated computer-mediated interactions. These methods were developed originally to study interactions involving teams composed of architecture, engineering, and construction management students as part of the AEC Global Teamwork course offered at Stanford University in collaboration with universities worldwide since 1993. The methods stress the value of using ethnographic approaches, particularly the role that both discourse and workspace have (...) in developing the communication processes involved in the interactions. We used the AEC Global Teamwork course as a testbed and focused on issues regarding the nature of the communication act in building design projects when mediated by computers. We successfully tested these new methods and present the preliminary results. (shrink)

Organisations have eagerly adopted the new opportunities provided by distributed computing technology. These opportunities have also created new dependency on the technology and threats of technical problems. Information technology (IT) management has to choose its position towards these new technical risks. Should the problems be prevented proactively in advance or settled reactively afterwards?This paper draws conclusions from an action research case study aimed at proactive versus reactive end-user support. Between 1994 and 1997 one of the business units in (...) Nokia Telecommunications required a new approach for its distributed information systems (IS) to facilitate rapid organisational growth. The distributed IS and its end-user support were established and organised during a 30-month re-engineering process.These results provide a new view to the dependencies between business processes and IT. The new distributed IT has become, often insidiously, a necessity for vital business processes. Therefore, risk management should be adopted as a standard tool for IS management to identify such dependencies. Proactive actions should be aimed at those areas where IT-related business risks are identified. Proactivity should be supplemented by reactive support to provide daily assistance for the end-users. (shrink)

Science is studied in very different ways by historians, philosophers, psychologists, and sociologists. Not only do researchers from different fields apply markedly different methods, they also tend to focus on apparently disparate aspects of science. At the farthest extremes, we find on one side some philosophers attempting logical analyses of scientific knowledge, and on the other some sociologists maintaining that all knowledge is socially constructed. This paper is an attempt to view history, philosophy, psychology, and sociology of science from a (...) unified perspective. (shrink)

Norms provide a valuable mechanism for establishing coherent cooperative behaviour in decentralised systems in which there is no central authority. One of the most influential formulations of norm emergence was proposed by Axelrod :1095–1111, 1986). This paper provides an empirical analysis of aspects of Axelrod’s approach, by exploring some of the key assumptions made in previous evaluations of the model. We explore the dynamics of norm emergence and the occurrence of norm collapse when applying the model over extended durations. It (...) is this phenomenon of norm collapse that can motivate the emergence of a central authority to enforce laws and so preserve the norms, rather than relying on individuals to punish defection. Our findings identify characteristics that significantly influence norm establishment using Axelrod’s formulation, but are likely to be of importance for norm establishment more generally. Moreover, Axelrod’s model suffers from significant limitations in assuming that private strategies of individuals are available to others, and that agents are omniscient in being aware of all norm violations and punishments. Because this is an unreasonable expectation, the approach does not lend itself to modelling real-world systems such as online networks or electronic markets. In response, the paper proposes alternatives to Axelrod’s model, by replacing the evolutionary approach, enabling agents to learn, and by restricting the metapunishment of agents to cases where the original defection is observed, in order to be able to apply the model to real-world domains. This work can also help explain the formation of a “social contract” to legitimate enforcement by a central authority. (shrink)

In order to benefit from the advantages of localist coding, neural models that feature winner-take-all representations at the top level of a network hierarchy must still solve the computational problems inherent in distributed representations at the lower levels.

We are quickly passing through the historical moment when people work in front of a single computer, dominated by a small CRT and focused on tasks involving only local information. Networked computers are becoming ubiquitous and are playing increasingly significant roles in our lives and in the basic infrastructure of science, business, and social interaction. For human-computer interaction o advance in the new millennium we need to better understand the emerging dynamic of interaction in which the focus task is no (...) longer confined to the desktop but reaches into a complex networked world of information and computer-mediated interactions. We think the theory of distributed cognition has a special role to play in understanding interactions between people and technologies, for its focus has always been on whole environments: what we really do in them and how we coordinate our activity in them. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human-computer interaction, sketch an integrated research framework, and use selections from our earlier work to suggest how this framework can provide new opportunities in the design of digital work materials. (shrink)

We study the computational complexity of the universal and quasi-equational theories of classes of bounded distributive lattices with a negation operation, i.e., a unary operation satisfying a subset of the properties of the Boolean negation. The upper bounds are obtained through the use of partial algebras. The lower bounds are either inherited from the equational theory of bounded distributive lattices or obtained through a reduction of a global satisfiability problem for a suitable system of propositional modal logic.

The present article examines the potential effects on the translation process of working interactively with a translation memory system, a tool for storing and sharing previous translations. A TM system automatically divides the source text into sentences presented to the translator one-by-one. Based on observations made in an empirical study of six professional translators and six translation students, it is argued that full sentences do not constitute a central cognitive processing category in translation, and that the sentence-by-sentence presentation inherent in (...) TM systems therefore creates an unnaturally strong focus on the sentence, which affects the very task of translation. Particular attention is given to the impact of the use of TM systems on the informants’ revision behaviour and their tendency to change the sentence structure. (shrink)

Deep learning models are powerful tools for representing the complex learning processes and decision-making strategies used by humans. Such neural network models make fewer assumptions about the underlying mechanisms thus providing experimental flexibility in terms of applicability. However, this comes at the cost of involving a larger number of parameters requiring significantly more data for effective learning. This presents practical challenges given that most cognitive experiments involve relatively small numbers of subjects. Laboratory collaborations are a natural way to increase overall (...) dataset size. However, data sharing barriers between laboratories as necessitated by data protection regulations encourage the search for alternative methods to enable collaborative data science. Distributed learning, especially federated learning, which supports the preservation of data privacy, is a promising method for addressing this issue. To verify the reliability and feasibility of applying FL to train neural networks models used in the characterization of decision making, we conducted experiments on a real-world, many-labs data pool including experiment data-sets from ten independent studies. The performance of single models trained on single laboratory data-sets was poor. This unsurprising finding supports the need for laboratory collaboration to train more reliable models. To that end we evaluated four collaborative approaches. The first approach represents conventional centralized learning and is the optimal approach but requires complete sharing of data which we wish to avoid. The results however establish a benchmark for the other three approaches, federated learning, incremental learning, and cyclic incremental learning. We evaluate these approaches in terms of prediction accuracy and capacity to characterize human decision-making strategies. The FL-based model achieves performance most comparable to that of the CL-based model. This indicates that FL has value in scaling data science methods to data collected in computational modeling contexts when data sharing is not convenient, practical or permissible. (shrink)

Preoperative diagnosis of gastric cancer and primary gastric lymphoma is challenging and has important clinical significance. Inspired by the inductive reasoning learning of the human brain, transfer learning can improve diagnosis performance of target task by utilizing the knowledge learned from the other domains (source domain). However, most studies focus on single-source transfer learning and may lead to model performance degradation when a large domain shift exists between the single-source domain and target domain. By simulating the multi-modal information learning and (...) transfer mechanism of human brain, this study designed a multisource transfer learning feature extraction and classification framework, which can enhance the prediction performance of the target model by using multisource medical data (domain). First, this manuscript designs a feature extraction network that takes the maximum mean difference based on the Wasserstein distance as an adaptive measure of probability distribution and extracts the domain-specific invariant representations between source and target domain data. Then, aiming at the random generation of parameters bringing uncertainties to prediction accuracy and generalization ability of extreme learning machine network, the 1-norm regularization is used to implement sparse constraints of the output weight matrix and improve the robustness of the model. Finally, some experiments are carried out on the data of two medical centers. The experimental results show that the area under curves (AUCs) of the method are 0.958 and 0.929 in the two validation cohorts, respectively. The method in this manuscript can provide doctors with a better diagnostic reference, which has certain practical significance. (shrink)

This paper explores the implications of extended and distributed cognition theory for our notions of personal identity. On an extended and distributed approach to cognition, external information is under certain conditions constitutive of memory. On a narrative approach to personal identity, autobiographical memory is constitutive of our diachronic self. In this paper, I bring these two approaches together and argue that external information can be constitutive of one’s autobiographical memory and thus also of one’s diachronic self. To develop (...) this claim, I draw on recent empirical work in human-computer interaction, looking at lifelogging technologies in both healthcare and everyday contexts. I argue that personal identity can neither be reduced to psychological structures instantiated by the brain nor by biological structures instantiated by the organism, but should be seen as an environmentally-distributed and relational construct. In other words, the complex web of cognitive relations we develop and maintain with other people and technological artifacts partly determines our self. This view has conceptual, methodological, and normative implications: we should broaden our concepts of the self as to include social and artifactual structures, focus on external memory systems in the (empirical) study of personal identity, and not interfere with people’s distributed minds and selves. (shrink)

Distributed cognition refers to processes which are (i) cognitive and (ii) distributed across multiple agents or devices rather than performed by a single agent. Distributed cognition has attracted interest in several fields ranging from sociology and law to computer science and the philosophy of science. In this paper, I discuss distributed cognition from a social-choice-theoretic perspective. Drawing on models of judgment aggregation, I address two questions. First, how can we model a group of individuals as a (...) distributed cognitive system? Second, can a group acting as a distributed cognitive system be ‘rational’ and ‘track the truth’ in the outputs it produces? I argue that a group’s performance as a distributed cognitive system depends on its ‘aggregation procedure’ – its mechanism for aggregating the group members’ inputs into collective outputs – and I investigate the properties of an aggregation procedure that matter. (shrink)

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony . This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply (...) the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. (shrink)

This paper proposes an analytical framework for the analysis of organizational cognition that borrows from distributed and ecological cognition. In so doing, we take a case study featuring a decision on the topic of agreeing on a set point in the agenda of a meeting. It is through the analysis of a few minutes of video-recording used in the case that enables us to demonstrate the power of applying distributed and ecological cognition to organizing processes. Cognitive mechanism, resources, (...) and processes are identified within this combined framework. Mechanisms are described as “socio-material” (CM1)—where “people” and “artifacts” are the related cognitive resources—and as “conceptual” (CM2)—with “group” identity, “topic” understanding, meaning of “procedures,” and perception of “time” as resources. Processes are defined as “coupling,” “de-coupling,” and “un-coupled” depending on the type of relation in place. Finally, the paper presents an agent-based computational simulation to demonstrate the potentials of operationalizing this approach. (shrink)

1. Argumentation, by considering arguments and their interactions, is a way of reasoning that has proven successful in many contexts, for instance, in multi-agent applications (Carrera & Iglesias,...

Recently predominant forms of anti-realism claim that all truths are knowable. We argue that in a logical explanation of the notion of knowability more attention should be paid to its epistemic part. Especially very useful in such explanation are notions of group knowledge. In this paper we examine mainly the notion of distributed knowability and show its effectiveness in the case of Fitch’s paradox. Proposed approach raised some philosophical questions to which we try to find responses. We also show (...) how we can combine our point of view on Fitch’s paradox with the others. Next we give an answer to the question: is distributed knowability factive? At the end, we present some details concerning a construction of anti-realist modal epistemic logic. (shrink)

The human conceptual system comprises simulated information of sensorimotor experience and linguistic distributional information of how words are used in language. Moreover, the linguistic shortcut hypothesis predicts that people will use computationally cheaper linguistic distributional information where it is sufficient to inform a task response. In a pre‐registered category production study, we asked participants to verbally name members of concrete and abstract categories and tested whether performance could be predicted by a novel measure of sensorimotor similarity (based on an 11‐dimensional (...) representation of sensorimotor strength) and linguistic proximity (based on word co‐occurrence derived from a large corpus). As predicted, both measures predicted the order and frequency of category production but, critically, linguistic proximity had an effect above and beyond sensorimotor similarity. A follow‐up study using typicality ratings as an additional predictor found that typicality was often the strongest predictor of category production variables, but it did not subsume sensorimotor and linguistic effects. Finally, we created a novel, fully grounded computational model of conceptual activation during category production, which best approximated typical human performance when conceptual activation was allowed to spread indirectly between concepts, and when candidate category members came from both sensorimotor and linguistic distributional representations. Critically, model performance was indistinguishable from typical human performance. Results support the linguistic shortcut hypothesis in semantic processing and provide strong evidence that both linguistic and grounded representations are inherent to the functioning of the conceptual system. All materials, data, and code are available at https://osf.io/vaq56/. (shrink)

Distributional semantics is an area of corpus linguistics and computational linguistics that seeks to model the meanings of words by producing a semantic space that captures the distributional properties of those words within a corpus. In this paper, I provide an overview of distributional semantic models, including a broad sketch of how such models are constructed. I then outline the reasons for and against the claim that distributional semantic models can serve as a theory of meaning, paying special attention to (...) those within the field who have defended this claim. Finally, I conclude by arguing that despite the fact that such models are holistic, they nevertheless avoid the objections raised against holistic theories of meaning, particularly from Fodor & Lepore (1992) (Holism: a shopper’s guide. Blackwell, 1992) and Fodor & Lepore (1999). (shrink)

We present a series of three analyses of young children's linguistic input to determine the distributional information it could plausibly offer to the process of grammatical category learning. Each analysis was conducted on four separate corpora from the CHILDES database (MacWhinney, 2000) of speech directed to children under 2;5. We showthat, in accord with other findings, a distributional analysis which categorizeswords based on their co‐occurrence patterns with surroundingwords successfully categorizes the majority of nouns and verbs. In Analyses 2 and 3, (...) we attempt to make our analyses more closely relevant to natural language acquisition by adopting more realistic assumptions about howyoung children represent their input. In Analysis 2, we limit the distributional context by imposing phrase structure boundaries, and find that categorization improves even beyond that obtained from less limited contexts. In Analysis 3, we reduce the representation of input elements which young children might not fully process and we find that categorization is not adversely affected: Although noun categorization is worse than in Analyses 1 and 2, it is still good; and verb categorization actually improves. Overall, successful categorization of nouns and verbs is maintained across all analyses. These results provide promising support for theories of grammatical category formation involving distributional analysis, as long as these analyses are combined with appropriate assumptions about the child learner's computational biases and capabilities. (shrink)

Many open networks, distributed computing systems, and infrastructure management systems face a common problem: how to distribute a collectivised set of resources amongst a set of autonomous agents of heterogenous provenance. One approach is for the agents themselves to self-organise the allocation of resources with respect to a set of agreed conventional rules; but given an allocation scheme which maps resources to those agents and a set of rules for determining that allocation scheme, some natural questions arise—Is this (...) allocation fair? Is the allocation method effective? Is it efficient? Are the decision makers accountable? In this paper, we argue that some answers to these questions can be found in the formal characterisation of different aspects of ‘justice’ and that these different aspects need a principled operationalisation as policies for system management. We present a formal model and some experimental results, concluding that the different aspects are all inter-connected and that what is required is a comprehensive research programme in computational justice. (shrink)

A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human‐like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content‐specific and non‐content‐specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two takes (...) advantage of the complementary costs and benefits of each. It also offers a better model of human cognitive competence. (shrink)

Arising in the study of Quantum Logics, PBZ $$^{*}$$ -lattices are the paraorthomodular Brouwer–Zadeh lattices in which the pairs of elements with their Kleene complements satisfy the Strong De Morgan condition with respect to the Brouwer complement. They form a variety $$\mathbb {PBZL}^{*}$$ which includes that of orthomodular lattices considered with an extended signature (by endowing them with a Brouwer complement coinciding with their Kleene complement), as well as antiortholattices (whose Brouwer complements are trivial). The former turn out to have (...) directly irreducible lattice reducts and, under distributivity, no nontrivial elements with bounded lattice complements, since the elements with bounded lattice complements coincide to the sharp elements in distributive PBZ $$^{*}$$ -lattices. The variety $$\mathbb {DIST}$$ of distributive PBZ $$^{*}$$ -lattices has an infinite ascending chain of subvarieties, and the variety generated by orthomodular lattices and antiortholattices has an infinity of pairwise disjoint infinite ascending chains of subvarieties. (shrink)

BackgroundIncreasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and processing (...) of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland’s geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations.MethodsTo conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform.ResultsFor our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation.ConclusionOur findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies. (shrink)

Humans are closely coupled with their environments. They rely on being ‘embedded’ to help coordinate the use of their internal cognitive resources with external tools and resources. Consequently, everyday cognition, even cognition in the absence of others, may be viewed as partially distributed. As cognitive scientists our job is to discover and explain the principles governing this distribution: principles of coordination, externalization, and interaction. As designers our job is to use these principles, especially if they can be converted to (...) metrics, in order to invent and evaluate candidate designs. After discussing a few principles of interaction and embedding I discuss the usefulness of a range of metrics derived from economics, computational complexity, and psychology. (shrink)

Purpose This paper aims to look at shifts in internet-related content and services economies, from audience labour economies to Web 2.0 user-generated content, and the emerging model of user computing power utilisation, powered by blockchain technologies. The authors look at and test three models of user computing power utilisation based on distributed computing two of which use cryptocurrency mining through distributed pool mining techniques, while the third is based on distributed computing of calculations (...) for scientific research. The three models promise benefits to their users, which the authors discuss throughout the paper, studying how they interplay with the three levels of the digital divide. Design/methodology/approach The goal of this article is twofold as follows: first to discuss how using the mining hype may reduce digital inequalities, and secondly to demonstrate how these services offer a new business model based on value rewarding in exchange for computational power, which would allow more online opportunities for people, and thus reduce digital inequalities. Finally, this contribution discusses and proposes a method for a fair revenue model for content and online service providers that uses user device computing resources or computational power, rather than their data and attention. The method is represented by a model that allows for consensual use of user computing resources in exchange for accessing content and using software tools and services, acting essentially as an alternative online business model. Findings Allowing users to convert their devices’ computational power into value, whether through access to services or content or receiving cryptocurrency and payments in return for providing services or content or direct computational powers, contributes to bridging digital divides, even at fairly small levels. Secondly, the advent of blockchain technologies is shifting power relations between end-users and content developers and service providers and is a necessity for the decentralisation of internet and internet services. Originality/value The article studies the effect of services that rely on distributed computing and mining on digital inequalities, by looking at three different case studies – Coinhive, Gridcoin and Cryptotab – that promise to provide value in return for using computing resources. The article discusses how these services may reduce digital inequalities by affecting the three levels of the digital divide, namely, access to information and communication technologies, skills and motivations in using ICTs and capacities in using ICTs to get concrete benefits. (shrink)

Despite the intrinsic complexity of integrating individual, social and technologically supported intelligence, the paper proposes a relatively simple ‘connectionist’ framework for conceptualizing distributed cognitive systems. Shared information sources (documents) are represented as nodes connected by links of variable strength, which increases as the documents co-occur in the usage patterns. This learning procedure captures and exploits its users’ implicit knowledge to help them find relevant information, thus supporting an unconscious form of exchange. These principles are applied to a concrete problem (...) domain: architects sharing design knowledge through a database of associatively connected building projects. (shrink)

Since the cognitive revolution, psychologists have developed formal theories of cognition by thinking about the mind as a computer. However, this metaphor is typically applied to individual minds. Humans rarely think alone; compared to other animals, humans are curiously dependent on stores of culturally transmitted skills and knowledge, and we are particularly good at collaborating with others. Rather than picturing the human mind as an isolated computer, we can imagine each mind as a node in a vast distributed system. (...) Viewing human cognition through the lens of distributed systems motivates new questions about how humans share computation, when it makes sense to do so, and how we can build institutions to facilitate collaboration. (shrink)

DCPS is a connectionist production system interpreter that uses distributed representations. As a connectionist model it consists of many simple, richly interconnected neuron‐like computing units that cooperate to solve problems in parallel. One motivation for constructing DCPS was to demonstrate that connectionist models are capable of representing and using explicit rules. A second motivation was to show how “coarse coding” or “distributed representations” can be used to construct a working memory that requires far fewer units than the (...) number of different facts that can potentially be stored. The simulation we present is intended as a detailed demonstration of the feasibility of certain ideas and should not be viewed as a full implementation of production systems. Our current model only has a few of the many interesting emergent properties that we eventually hope to demonstrate: It is damage‐resistant, it performs matching and variable binding by massively parallel constraint satisfaction, and the capacity of its working memory is dependent on the similarity of the items being stored. (shrink)

The paper discusses ubiquitous computing and the conception of the self, especially the question how the self should be understood in the environment pervaded by ubiquitous computing, and how ubiquitous computing makes possible direct empathy where each person or self connected through the network has direct access to others’ thoughts and feelings. Starting from a conception of self, which is essentially distributed, composite and constituted through information, the paper argues that when a number of selves are (...) connected to one another in the ubiquitous computing network, a possibility opens up where the selves can directly communicate with one another. This has a potential finally to solve the problem of other minds, and in fact any philosophical conundrum based on the supposed distinction between self and the world. When selves have direct access to others’ thoughts and feelings, they know the content of others’ mental states directly without having to make inferences or employing some other indirect methods. As they are interconnected through the ubiquitous network, and as they are essentially constituted through information, the selves then are spread out across the network. What this implies is that any boundary between a self and another is not as hard and fast as hitherto may have been understood. Toward the end, the paper also discusses how freedom and autonomy are still possible in this ubiquitously networked world. (shrink)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in (...) accounts of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (shrink)

Recent trends towards an e-Science offer us the opportunity to think about the specific epistemological changes created by computational empowerment in scientific practices. In fact, we can say that a computational epistemology exists that requires our attention. By ‘computational epistemology’ I mean the computational processes implied or required to achieve human knowledge. In that category we can include AI, supercomputers, expert systems, distributed computation, imaging technologies, virtual instruments, middleware, robotics, grids or databases. Although several authors talk about the extended (...) mind and computational extensions of the human body, most of these proposals don’t analyze the deep epistemological implications of computer empowerment in scientific practices. At the same time, we must identify the principal concept for e-Science: Information . Why should we think about a new epistemology for e-Science? Because several processes exist around scientific information that require a good epistemological model to be understood. (shrink)

Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence and help. Connections (...) with human-computer interaction are also suggested. (shrink)

Forms of collective leadership, such as Distributed Leadership, have become increasingly important. The need for measurement of the variables involved in the delegation processes, represents a new challenge for organizations that want to ensure high-level working. The present research aimed to validate the Italian version of the Distributed Leadership Agency (DLA) and verify its applicability in different contexts. The study involved all the employees of an Italian public Hospital, which were selected to complete a survey on organizational perceptions. (...) The sample comprised 704 employees (doctors, nurses, clerks, staff workers, healthcare assistants, consultants, management). Multiple Confirmatory Factor Analyses (Maximum Likelihood) have been computed to explore the factorial structure of the DLA, along with associations with other work outcomes. Results clarified that the Italian DLA respects the tri-factorial structure of the construct, suggested by Yukl (2002), with good fit indexes and reliability; moreover, in line with the literature, DLA was strongly related to satisfaction, commitment, and trust. Results contribute to underline the robustness of the construct of distributed leadership agency in different cultural sectors, and provide a useful tool to be adopted in the Italian context. (shrink)

Eco-cognitive computationalism considers computation in context, following some of the main tenets advanced by the recent cognitive science views on embodied, situated, and distributed cognition. It is in the framework of this eco-cognitive perspective that we can usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities by the morphological features: ignorant bodies can be domesticated to become useful “mimetic bodies”, that is able to render (...) an intertwined computation simpler, resorting to that “simplexity” of animal embodied cognition, which represents one of the main quality of organic agents. Through eco-cognitive computationalism we can clearly acknowledge that the concept of computation changes, depending on historical and contextual causes, and we can build an epistemological view that illustrates the “emergence” of new kinds of computations, such as the one regarding morphological computation. This new perspective shows how the computational domestication of ignorant entities can originate new unconventional cognitive embodiments. In the last part of the article I will introduce the concept of overcomputationalism, showing that my proposed framework helps us see the related concepts of pancognitivism, paniformationalism, and pancomputationalism in a more naturalized and prudent perspective, avoiding the excess of old-fashioned ontological or metaphysical overstatements. (shrink)

A computational modeling approach was used to test one possible explanation for the limited capacity of the subitizing phenomenon. Most existing models of this phenomenon associate the subitizing span with an assumed structural limitation of the human information processing system. In contrast, we show how this limit might emerge as the combinatorics of the space of enumeration problems interacts with the human cognitive architecture in the context of an enumeration task. Subitizing‐like behavior was generated in two different models of enumeration, (...) one based on the ACT‐R cognitive architecture and the other based on the principles of parallel distributed processing (PDP). Our results provide good qualitative fits to results obtained in a variety of empirical studies. (shrink)