Cognitive scientists have long used distributional semantic representations of categories. The predominant approach uses distributional representations of category‐denoting nouns, such as “city” for the category city. We propose a novel scheme that represents categories as prototypes over representations of names of its members, such as “Barcelona,” “Mumbai,” and “Wuhan” for the category city. This name‐based representation empirically outperforms the noun‐based representation on two experiments (modeling human judgments of category relatedness and predicting category membership) with particular improvements for ambiguous (...) nouns. We discuss the model complexity of both classes of models and argue that the name‐based model has superior explanatory potential with regard to concept acquisition. (shrink)

Vector-based models of word meaning have become increasingly popular in cognitive science. The appeal of these models lies in their ability to represent meaning simply by using distributional information under the assumption that words occurring within similar contexts are semantically similar. Despite their widespread use, vector-based models are typically directed at representing words in isolation, and methods for constructing representations for phrases or sentences have received little attention in the literature. This is in marked contrast to (...) experimental evidence (e.g., in sentential priming) suggesting that semantic similarity is more complex than simply a relation between isolated words. This article proposes a framework for representing the meaning of word combinations in vector space. Central to our approach is vector composition, which we operationalize in terms of additive and multiplicative functions. Under this framework, we introduce a wide range of composition models that we evaluate empirically on a phrase similarity task. (shrink)

Page argues that localist models can be applied to a number of problems that are difficult for distributed models. However, it is easy to find examples where the opposite is true. This commentary illustrates the superiority of distributed models in the domain of artificial grammar learning, a paradigm widely used to investigate implicit learning.

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has (...) been underappreciated. We compare the representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

In this paper we present Drama, a distributed model of analogical mapping that integrates semantic and structural constraints on constructing analogies. Specifically, Drama uses holographic reduced representations (Plate, 1994), a distributed representation scheme, to model the effects of structure and meaning on human performance of analogical mapping. Drama is compared to three symbolic models of analogy (SME, Copycat, and ACME) and one partially distributed model (LISA). We describe Drama's performance on a number of example analogies and assess the model (...) in terms of neurological and psychological plausibility. We argue that Drama's successes are due largely to integrating structural and semantic constraints throughout the mapping process. We also claim that Drama is an existence proof of using distributed representations to model high‐level cognitive phenomena. (shrink)

Words are not just labels for conceptual categories. Words construct conceptual categories, frame situations and influence behavior. Where do they get their meaning? This book describes how words acquire their meaning. The author argues that mechanisms based on associations, pattern detection, and feature matching processes explain how words acquire their meaning from experience and from language alike. Such mechanisms are summarized by the distributional hypothesis, a computational theory of meaning originally applied to word occurrences only, and hereby extended to (...) extra-linguistic contexts. By arguing in favor of the cognitive foundations of the distributional hypothesis, which suggests that words that appear in similar contexts have similar meaning, this book offers a theoretical account for word meaning construction and extension in first and second language that bridges empirical findings from cognitive and computer sciences. Plain language and illustrations accompany the text, making this book accessible to a multidisciplinary academic audience. (shrink)

Recent work on the role of models in science has revealed a great many kinds of models performing many different roles. In this paper I suggest that one can find much unity among all this diversity by thinking of many models as being components of distributed cognitive systems. I begin by distinguishing the relevant notion of a distributed cognitive system and then give examples of different kinds of models that can be thought of as functioning as (...) components of such systems. These include both physical and abstract models. After considering several objections, I conclude by locating distributed cognition within larger movements in contemporary cognitive science. (shrink)

(2013). Distributed intentionality: A model of intentional behavior in humans. Philosophical Psychology: Vol. 26, No. 2, pp. 267-290. doi: 10.1080/09515089.2011.641743.

We prove the Finite Model Property (FMP) for Distributive Full Lambek Calculus ( DFL ) whose algebraic semantics is the class of distributive residuated lattices ( DRL ). The problem was left open in [8, 5]. We use the method of nuclei and quasi–embedding in the style of [10, 1].

The function of groups as information processors is increasingly being recognised in a number of theories of group cognition. A theme of many of these is an emphasis on sharing cognition. This paper extends current conceptualisations of groups by critiquing the focus on shared cognition and emphasising the distribution of cognition in groups. In particular, it develops an account of the distribution of one cognitive construct, mental models. Mental models have been chosen as a focus because they are (...) used in a number of theories of high level cognition from different areas of research such as cognitive science and human factors and so the implication of this development is wide reaching. This paper reviews the unconnected literatures on distributed cognition and mental models and integrates them in order to extend the theory of mental models to distributed cognitive systems such as groups. The distributed cognition literature is reviewed and the importance of considering the group as single cognitive system is adopted. A range of mental model theories are reviewed leading to the conclusion that they all have, in some form, the central feature of a mapping onto the cognitive system. Combining these two ideas, it is proposed that the model can be a mapping onto the whole group, if the information is distributed appropriately and the connections between parts of the model maintained through communication. This cognitive construct is referred to as a distributed mental model. Implications and applications of this theory are discussed. (shrink)

A number of (insect) parasitoids have been found to avoid superparasitism, i.e., these parasitoids distribute their eggs more evenly over the available hosts than might be expected from chance only. By doing so each parasitoid individual ensures a greater probability of survival for its offspring as a result of a reduced within-host-competition.Recently a number of mathematical models have been developed, describing the distribution of the parasitoid eggs in the hosts. This paper gives a survey of these models, placing (...) them within one and the same mathematical framework. An essential conceptual distinction, neglected up to now, emerges: parasitoids can either react to the number of previous visits to a particular host, or they can react to the number of eggs already present in that host. (shrink)

A simple numerical procedure is presented for the problem of estimating the parameters of models for the distribution of eggs oviposited in a host. The modelling is extended to incorporate both host density and time dependence to produce a remarkably parsimonious structure with only seven parameters to describe a data set of over 3,000 observations. This is further refined using a mixed model to accommodate several large outliers. Both models show that the level of superparasitism declines with increasing (...) host density, and the rate declines over time. It is proposed that the differing behaviours represented by the mixed model may reflect a balance between behavioural strategies of different selective benefit. (shrink)

This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive (...) science that construes cognition as occurring in a complex distributed system comprising people and artifacts, I argue that reasoning with model systems is a constraint satisfaction process involving co-construction, manipulation, and revision of mental and physical models. (shrink)

Within analytic philosophy, the existence of collective knowledge has been motivated by means of two apparently distinct, and in direct competition with one another, theoretical approaches: (i) the commitment model and (ii) the distributed model. This paper agues, however, that to fully account for collaborative knowledge—i.e., a special kind of collective knowledge—both models are required. In other words, there is at least one kind of collective knowledge, the account of which requires treating the two models not as competitors (...) but as complementary to each other. If that’s correct, not only can we gain a deeper understanding of the specifics surrounding collaborative knowledge but also a clearer picture of the broader debate surrounding collective knowledge. (shrink)

Philosophical disagreement about justice ranges over at least two questions. The most immediate is a substantial question, concerning the conditions under which particular distributive arrangements can be said to be just or unjust. The second, deeper, question concerns the nature of justice itself. What is justice? Here we can distinguish three views. First, justice as mutual advantage sees justice as essentially a matter of the outcome of a bargain. There are times when two parties can both be better off by (...) making some sort of agreement. Justice, on this view, concerns the distribution of the benefits and burdens of the agreement. Second, justice as reciprocity takes a different approach, looking not at bargaining but at the idea of a fair return or just price, attempting to capture the idea of justice as equal exchange. Finally justice as impartiality sees justice as ‘taking the other person’s point of view’ asking ‘how would you like it if it happened to you?’ Each model has significantly different consequences for the question of when issues of justice arise and how they should be settled. It is interesting to consider whether any of these models of justice could regulate behaviour between non-human animals. (shrink)

Matrix models are widely used in biology to predict the temporal evolution of stage-structured populations. One issue related to matrix models that is often disregarded is the sampling variability. As the sample used to estimate the vital rates of the models are of finite size, a sampling error is attached to parameter estimation, which has in turn repercussions on all the predictions of the model. In this study, we address the question of building confidence bounds around the (...) predictions of matrix models due to sampling variability. We focus on a density-dependent Usher model, the maximum likelihood estimator of parameters, and the predicted stationary stage vector. The asymptotic distribution of the stationary stage vector is specified, assuming that the parameters of the model remain in a set of the parameter space where the model admits one unique equilibrium point. Tests for density-dependence are also incidentally provided. The model is applied to a tropical rain forest in French Guiana. (shrink)

There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual (...) models do not provide mechanistic explanations by themselves. Instead, individual models are always used to complement a huge body of background information and pre-existing models about the target system. With this in mind, I argue that mechanistic explanations are distributed across sets of different, and sometimes contradictory, scientific models. Each of these models contributes limited, but essential, information to the same mechanistic explanation, but none can be considered a mechanistic explanation in isolation of the others. (shrink)

The distributed temporal logic (DTL) is a logic for reasoning about temporal properties of distributed systems from the local point of view of the system’s agents, which are assumed to execute sequentially and to interact by means of synchronous event sharing. Different versions of DTL have been provided over the years for a number of different applications, reflecting different perspectives on how non-local information can be accessed by each agent. In this paper, we propose an automata-theoretic model checking algorithm for (...) DTL. To this end, we propose a notion of distributed transition system that will be used to specify the system to be verified. The properties that the system should meet are specified in DTL. In order to capture the models of these properties, we propose the notions of generalized distributed Büchi automaton and of distributed Büchi automaton. With these concepts, we are able to adapt results from automata-theoretic approaches to model checking in LTL to the distributed case. (shrink)

This article presents a new model aimed at predicting behavior in games involving a randomized allocation procedure. It is designed to capture the relative importance and interaction between procedural justice (defined crudely in terms of the difference between one’s expected payoff and average expected payoff in the group) and distributive justice (difference between own and average actual payoffs). The model is applied to experimental games, including “randomized” variations of simple sequential bargaining games, and delivers qualitatively correct predictions. In view of (...) the model redistribution of income can be seen as a substitute for vertical social mobility. This contributes to the explanation of greater demand for redistribution in European countries vis-a-vis the United States. I conclude with suggestions for further verification of the model and possible extensions. (shrink)

We present a model of the distribution of labour in science. Such models tend to rely on the mechanism of the invisible hand . Our analysis starts from the necessity of standards in distributed processes and the possibility of multiple standards in science. Invisible hand models turn out to have only limited scope because they are restricted to describing the atypical single-standard case. Our model is a generalisation of these models to J standards; single-standard models such (...) as Kitcher are a limiting case. We introduce and formalise this model, demonstrate its dynamics and conclude that the conclusions commonly derived from invisible hand models about the distribution of labour in science are not robust against changes in the number of standards. (shrink)

International borders concentrate opportunities in some societies while limiting them in others. Borders also prevent those in the less favored societies from gaining access to opportunities available in the more favored ones. Both distributive effects of borders are treated here within a comprehensive framework. I argue that each state should have broad discretion under international law to grant or deny entry to immigration seekers; but more favored countries that find themselves under immigration pressure should be legally obligated to fund development (...) assistance for countries that generate immigration pressure. Funding should be subject to conditions of fair and effective use in recipient countries, and should aim at a near-term target of immigration-pressure equilibrium. Equilibrium obtains between two countries when, given appropriate background circumstances, the same proportion of individuals in each manifests a preference to migrate to the other. If meeting the equilibrium target in the short term would be to the long-term disadvantage of the worst-off countries, then a Pareto-superior alternative target supersedes. It mandates development assistance at the level that yields the most favorable human development projections for the worstoff countries. An implementable set of institutions is described that can achieve the equilibrium goal in the long term without unduly sacrificing other important ends, including economic growth, political stability, cultural integrity, the political autonomy of distinct societies, and their proper accountability for policy choices. Key Words: global justice • immigration • borders • development • distributive justice • development assistance • equality • international law • cosmopolitanism. (shrink)

A simple numerical procedure is presented for the problem of estimating the parameters of models for the distribution of eggs oviposited in a host. The modelling is extended to incorporate both host density and time dependence to produce a remarkably parsimonious structure with only seven parameters to describe a data set of over 3,000 observations. This is further refined using a mixed model to accommodate several large outliers. Both models show that the level of superparasitism declines with increasing (...) host density, and the rate declines over time. It is proposed that the differing behaviours represented by the mixed model may reflect a balance between behavioural strategies of different selective benefit. (shrink)

A simple numerical procedure is presented for the problem of estimating the parameters of models for the distribution of eggs oviposited in a host. The modelling is extended to incorporate both host density and time dependence to produce a remarkably parsimonious structure with only seven parameters to describe a data set of over 3,000 observations. This is further refined using a mixed model to accommodate several large outliers. Both models show that the level of superparasitism declines with increasing (...) host density, and the rate declines over time. It is proposed that the differing behaviours represented by the mixed model may reflect a balance between behavioural strategies of different selective benefit. (shrink)

A simple numerical procedure is presented for the problem of estimating the parameters of models for the distribution of eggs oviposited in a host. The modelling is extended to incorporate both host density and time dependence to produce a remarkably parsimonious structure with only seven parameters to describe a data set of over 3,000 observations. This is further refined using a mixed model to accommodate several large outliers. Both models show that the level of superparasitism declines with increasing (...) host density, and the rate declines over time. It is proposed that the differing behaviours represented by the mixed model may reflect a balance between behavioural strategies of different selective benefit. (shrink)

This article revisits the macroeconomic foundations and political economy of national growth models. It argues that the neo-Kaleckian model, which inspired the emergent growth model perspective and focuses primarily on the functional income distribution, can be usefully complemented by theories of private household consumption that focus on the personal distribution of income. The examples of the export-led and debt-led growth models of Germany and the United States, respectively, show how institutional differences help to explain why different countries developed (...) different patterns of income distribution and how income distribution and institutions interacted to generate financial imbalances in different sectors of the economy. (shrink)

Hebbian cell-assembly theory and attractor networks are good starting points for modeling cortical processing. Detailed cell models can be useful in understanding the dynamics of attractor networks. Cell assemblies are likely to be distributed, with the cortical column as the local processing unit. Synaptic memory may be dominant in all but the first couple of seconds.

We define a variant of the standard Kripke semantics for intuitionistic logic, motivated by the connection between constructive logic and the Medvedev lattice. We show that while the new semantics is still complete, it gives a simple and direct correspondence between Kripke models and algebraic structures such as factors of the Medvedev lattice.

Global supply chains often distribute value inequitably among the Global North and South. This perpetuates poverty and contributes to indecent work in raw material-producing countries, thus creating challenges to sustainable development. For decades, corporate social responsibility, social entrepreneurship, and sustainable business model innovations have aimed to distribute value more equitably across global value chains, for instance via fair trade, alternative trade, and direct trade. This article examines a novel and hitherto understudied innovation for equitable value distribution in global supply chains: (...) “value chain profit sharing.” We draw on interview and archival data from two cases of social entrepreneurs working in the coffee sector to develop a generalized model. One of the model's key features is that the entrepreneur pays suppliers in multiple installments that reflect market conditions (as opposed to a single lump sum based on prediction). We show how this can increase value creation, appropriation, and equitable distribution. Although our research suggests that this model may be highly contingent on leaders' skills, resources, sense of place, and accountability to suppliers, we find no evidence that its applications are limited to specific countries or sectors. Our research further extends extant theory by showing how “value chain profit sharing” may relieve some of the tensions often associated with sustainable business models, including distributing value to suppliers while maintaining financial solvency; creating value while pursuing a social mission; providing benefits to suppliers without curtailing their market opportunities; responding to market conditions while maintaining commitments to suppliers; and scaling without diluting benefits. It thereby contributes to the literatures on sustainable business model innovations, equitable value distribution in global supply chains, novel application of revenue-sharing contracts, and innovative methods of profit sharing. It furthermore provides actionable guidance for social entrepreneurs, corporate social responsibility practitioners, and supplier cooperatives aiming to achieve more equitable value distribution and sustainable supply chains. (shrink)

Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in many different aspects of language learning, including phonetic categories, using phonemic distinctions in word learning, and discovering non-adjacent relations. On the surface, these different aspects share few commonalities. (...) Despite this, we demonstrate that the same computational framework can account for learning in all of these tasks. These results support two conclusions. The first is that much, and perhaps all, of distributional statistical learning can be explained by the same underlying set of processes. The second is that some aspects of language can be learned due to domain-general characteristics of memory. (shrink)

In this paper my goal is to extend my earlier discussion, at least in a preliminary way, to two additional areas – fairness and stealing. In doing so, I will consider whether the existing research is compatible with my Mixed Trait model, or whether instead it gives me reason to be concerned with how broadly applicable the model really is. My conclusion will be that the results are, so to speak, a mixed bag. With respect to fairness research, some careful (...) conceived studies have been done which do in fact provide additional support for my model. But in the area of research of stealing, it will turn out that we are badly in need of new behavioral studies before we can draw any reasonable conclusions about people’s characters in this area. (shrink)