Order:
See also
Shimon Edelman
Cornell University
  1. Computing the Mind: How the Mind Really Works.Shimon Edelman - 2008 - Oxford University Press.
    The account that Edelman gives in this book is accessible, yet unified and rigorous, and the big picture he presents is supported by evidence ranging from ...
    Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark   26 citations  
  2. Representation is Representation of Similarities.Shimon Edelman - 1998 - Behavioral and Brain Sciences 21 (4):449-467.
    Intelligent systems are faced with the problem of securing a principled (ideally, veridical) relationship between the world and its internal representation. I propose a unified approach to visual representation, addressing both the needs of superordinate and basic-level categorization and of identification of specific instances of familiar categories. According to the proposed theory, a shape is represented by its similarity to a number of reference shapes, measured in a high-dimensional space of elementary features. This amounts to embedding the stimulus in a (...)
    Direct download (12 more)  
     
    Export citation  
     
    Bookmark   34 citations  
  3.  74
    Representation, Similarity, and the Chorus of Prototypes.Shimon Edelman - 1995 - Minds and Machines 5 (1):45-68.
    It is proposed to conceive of representation as an emergent phenomenon that is supervenient on patterns of activity of coarsely tuned and highly redundant feature detectors. The computational underpinnings of the outlined concept of representation are (1) the properties of collections of overlapping graded receptive fields, as in the biological perceptual systems that exhibit hyperacuity-level performance, and (2) the sufficiency of a set of proximal distances between stimulus representations for the recovery of the corresponding distal contrasts between stimuli, as in (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   38 citations  
  4. System, Subsystem, Hive: Boundary Problems in Computational Theories of Consciousness.Tomer Fekete, Cees van Leeuwen & Shimon Edelman - 2016 - Frontiers in Psychology 7.
    A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i) would reveal to what extent a given system is conscious, (ii) would make it possible to compare not only different systems, but also the same system at different times, and (iii) would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  5.  96
    General Cognitive Principles for Learning Structure in Time and Space.Michael H. Goldstein, Heidi R. Waterfall, Arnon Lotem, Joseph Y. Halpern, Jennifer A. Schwade, Luca Onnis & Shimon Edelman - 2010 - Trends in Cognitive Sciences 14 (6):249-258.
  6.  32
    Learn Locally, Act Globally: Learning Language From Variation Set Cues.Luca Onnis, Heidi R. Waterfall & Shimon Edelman - 2008 - Cognition 109 (3):423.
    No categories
    Direct download (11 more)  
     
    Export citation  
     
    Bookmark   19 citations  
  7.  51
    On the Nature of Minds, Or: Truth and Consequences.Shimon Edelman - 2008 - Journal of Experimental and Theoretical Ai 20:181-196.
    Are minds really dynamical or are they really symbolic? Because minds are bundles of computations, and because computation is always a matter of interpretation of one system by another, minds are necessarily symbolic. Because minds, along with everything else in the universe, are physical, and insofar as the laws of physics are dynamical, minds are necessarily dynamical systems. Thus, the short answer to the opening question is “yes.” It makes sense to ask further whether some of the computations that constitute (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   14 citations  
  8.  65
    Towards a Computational Theory of Experience.Tomer Fekete & Shimon Edelman - 2011 - Consciousness and Cognition 20 (3):807-827.
    A standing challenge for the science of mind is to account for the datum that every mind faces in the most immediate – that is, unmediated – fashion: its phenomenal experience. The complementary tasks of explaining what it means for a system to give rise to experience and what constitutes the content of experience (qualia) in computational terms are particularly challenging, given the multiple realizability of computation. In this paper, we identify a set of conditions that a computational theory must (...)
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   9 citations  
  9.  91
    Learning a Generative Probabilistic Grammar of Experience: A Process‐Level Model of Language Acquisition.Oren Kolodny, Arnon Lotem & Shimon Edelman - 2014 - Cognitive Science 38 (4):227-267.
    We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  10.  64
    How Seriously Should We Take Minimalist Syntax?Shimon Edelman & Morten H. Christiansen - 2003 - Trends in Cognitive Sciences 7 (2):60-61.
  11.  53
    Towards Structural Systematicity in Distributed, Statically Bound Visual Representations.Shimon Edelman & Nathan Intrator - 2003 - Cognitive Science 23 (1):73-110.
    The problem of representing the spatial structure of images, which arises in visual object processing, is commonly described using terminology borrowed from propositional theories of cognition, notably, the concept of compositionality. The classical propositional stance mandates representations composed of symbols, which stand for atomic or composite entities and enter into arbitrarily nested relationships. We argue that the main desiderata of a representational system — productivity and systematicity — can (indeed, for a number of reasons, should) be achieved without recourse to (...)
    No categories
    Direct download (8 more)  
     
    Export citation  
     
    Bookmark   11 citations  
  12. Computational Theories of Object Recognition.Shimon Edelman - 1997 - Trends in Cognitive Sciences 1 (8):296-304.
    Direct download (8 more)  
     
    Export citation  
     
    Bookmark   10 citations  
  13.  56
    Constraining the Neural Representation of the Visual World.Shimon Edelman - 2002 - Trends in Cognitive Sciences 6 (3):125-131.
  14.  55
    How Seriously Should We Take Minimalist Syntax?Shimon Edelman - 2003 - Trends in Cognitive Sciences 7 (2):60-61.
    Lasnik’s review of the Minimalist program in syntax [1] offers cognitive scientists help in navigating some of the arcana of the current theoretical thinking in transformational generative grammar. One may observe, however, that this journey is more like a taxi ride gone bad than a free tour: it is the driver who decides on the itinerary, and questioning his choice may get you kicked out. Meanwhile, the meter in the cab of the generative theory of grammar is running, and has (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   10 citations  
  15.  30
    The (Lack of) Mental Life of Some Machines.Tomer Fekete & Shimon Edelman - 2012 - In Shimon Edelman, Tomer Fekete & Neta Zach (eds.), Being in Time: Dynamical Models of Phenomenal Experience. John Benjamins.. pp. 88--95.
    The proponents of machine consciousness predicate the mental life of a machine, if any, exclusively on its formal, organizational structure, rather than on its physical composition. Given that matter is organized on a range of levels in time and space, this generic stance must be further constrained by a principled choice of levels on which the posited structure is supposed to reside. Indeed, not only must the formal structure fit well the physical system that realizes it, but it must do (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  16.  48
    Bridging Computational, Formal and Psycholinguistic Approaches to Language.Shimon Edelman - unknown
    We compare our model of unsupervised learning of linguistic structures, ADIOS [1, 2, 3], to some recent work in computational linguistics and in grammar theory. Our approach resembles the Construction Grammar in its general philosophy (e.g., in its reliance on structural generalizations rather than on syntax projected by the lexicon, as in the current generative theories), and the Tree Adjoining Grammar in its computational characteristics (e.g., in its apparent affinity with Mildly Context Sensitive Languages). The representations learned by our algorithm (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   5 citations  
  17.  42
    Generalization to Novel Images in Upright and Inverted Faces.Shimon Edelman - unknown
    An image of a face depends not only on its shape, but also on the viewpoint, illumination conditions, and facial expression. A face recognition system must overcome the changes in face appearance induced by these factors. This paper investigate two related questions: the capacity of the human visual system to generalize the recognition of faces to novel images, and the level at which this generalization occurs. We approach this problems by comparing the identi cation and generalization capacity for upright and (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   5 citations  
  18.  15
    Juvenile Zebra Finches Learn the Underlying Structural Regularities of Their Fathers’ Song.Otília Menyhart, Oren Kolodny, Michael H. Goldstein, Timothy J. DeVoogd & Shimon Edelman - 2015 - Frontiers in Psychology 6.
  19.  35
    Automatic Acquisition and Efficient Representation of Syntactic Structures.Shimon Edelman - unknown
    The distributional principle according to which morphemes that occur in identical contexts belong, in some sense, to the same category [1] has been advanced as a means for extracting syntactic structures from corpus data. We extend this principle by applying it recursively, and by using mutual information for estimating category coherence. The resulting model learns, in an unsupervised fashion, highly structured, distributed representations of syntactic knowledge from corpora. It also exhibits promising behavior in tasks usually thought to require representations anchored (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   5 citations  
  20.  46
    Unsupervised Learning of Visual Structure.Shimon Edelman - unknown
    To learn a visual code in an unsupervised manner, one may attempt to capture those features of the stimulus set that would contribute significantly to a statistically efficient representation. Paradoxically, all the candidate features in this approach need to be known before statistics over them can be computed. This paradox may be circumvented by confining the repertoire of candidate features to actual scene fragments, which resemble the “what+where” receptive fields found in the ventral visual stream in primates. We describe a (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  21.  43
    Unsupervised Efficient Learning and Representation of Language Structure.Shimon Edelman - unknown
    We describe a linguistic pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of corpus data. This is achieved by compactly coding recursively structured constituent patterns, and by placing strings that have an identical backbone and similar context structure into the same equivalence class. The resulting representations constitute an efficient encoding of linguistic knowledge and support systematic generalization to unseen sentences.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  22.  40
    Characterizing Motherese: On the Computational Structure of Child-Directed Language.Shimon Edelman - unknown
    We report a quantitative analysis of the cross-utterance coordination observed in child-directed language, where successive utterances often overlap in a manner that makes their constituent structure more prominent, and describe the application of a recently published unsupervised algorithm for grammar induction to the largest available corpus of such language, producing a grammar capable of accepting and generating novel wellformed sentences. We also introduce a new corpus-based method for assessing the precision and recall of an automatically acquired generative grammar without recourse (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   4 citations  
  23.  29
    Unsupervised Context Sensitive Language Acquisition From a Large Corpus.Shimon Edelman - unknown
    We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. This paper addresses the issues of learning structured knowledge from a large-scale natural language data set, and of generalization to unseen text. The implemented algorithm represents sentences as paths on a graph whose vertices are words. Significant patterns, determined by recursive context-sensitive statistical inference, form new vertices. Linguistic constructions are represented by trees composed of significant patterns and (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  24.  24
    But Will It Scale Up? Not Without Representations.Shimon Edelman - 2003 - Adaptive Behavior 11:273-275.
  25.  9
    The Bottleneck May Be the Solution, Not the Problem.Arnon Lotem, Oren Kolodny, Joseph Y. Halpern, Luca Onnis & Shimon Edelman - 2016 - Behavioral and Brain Sciences 39.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  26.  10
    Identity, Immortality, Happiness: Pick Two.Shimon Edelman - 2018 - Journal of Evolution and Technology 28 (1):1-17.
    To the extent that the performance of embodied and situated cognitive agents is predicated on fore- thought;such agents must remember; and learn from; the past to predict the future. In complex; non-stationaryenvironments; such learning is facilitated by an intrinsic motivation to seek novelty. A significant part of anagent’s identity is thus constituted by its remembered distilled cumulative life experience; which the agent isdriven to constantly expand. The combination of the drive to novelty with practical limits on memorycapacity posits a problem. (...)
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  27.  8
    Towards Structural Systematicity in Distributed, Statically Bound Visual Representations.Shimon Edelman & Nathan Intrator - 2003 - Cognitive Science 27 (1):73-109.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   7 citations  
  28.  22
    A Productive, Systematic Framework for the Representation of Visual Structure.Shimon Edelman - unknown
    We describe a unified framework for the understanding of structure representation in primate vision. A model derived from this framework is shown to be effectively systematic in that it has the ability to interpret and associate together objects that are related through a rearrangement of common “middle-scale” parts, represented as image fragments. The model addresses the same concerns as previous work on compositional representation through the use of what+where receptive fields and attentional gain modulation. It does not require prior exposure (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  29.  37
    Being in Time.Shimon Edelman & Tomer Fekete - 2012 - In Shimon Edelman, Tomer Fekete & Neta Zach (eds.), Being in Time: Dynamical Models of Phenomenal Experience. John Benjamins. pp. 88--81.
  30.  72
    Being in Time: Dynamical Models of Phenomenal Experience.Shimon Edelman, Tomer Fekete & Neta Zach (eds.) - 2012 - John Benjamins.
    The chapters comprising this book represent a collective attempt on the part of their authors to redress this aberration.
    Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  31.  27
    Neural Spaces: A General Framework for the Understanding of Cognition?Shimon Edelman - 2001 - Behavioral and Brain Sciences 24 (4):664-665.
    A view is put forward, according to which various aspects of the structure of the world as internalized by the brain take the form of “neural spaces,” a concrete counterpart for Shepard's “abstract” ones. Neural spaces may help us understand better both the representational substrate of cognition and the processes that operate on it. [Shepard].
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  32.  57
    On Look-Ahead in Language: Navigating a Multitude of Familiar Paths.Shimon Edelman - unknown
    Language is a rewarding field if you are in the prediction business. A reader who is fluent in English and who knows how academic papers are typically structured will readily come up with several possible guesses as to where the title of this section could have gone, had it not been cut short by the ellipsis. Indeed, in the more natural setting of spoken language, anticipatory processing is a must: performance of machine systems for speech interpretation depends critically on the (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  33.  30
    Vision, Reanimated and Reimagined.Shimon Edelman - unknown
    The publication in 1982 of David Marr’s Vision has delivered a singular boost and a course correction to the science of vision. Thirty years later, cognitive science is being transformed by the new ways of thinking about what it is that the brain computes, how it does that, and, most importantly, why cognition requires these computations and not others. This ongoing process still owes much of its impetus and direction to the sound methodology, engaging style, and unique voice of Marr’s (...)
    Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  34.  51
    Trade-off Between Capacity and Generalization in a Model of Memory.Shimon Edelman - unknown
    Although computational considerations suggest that a resource-limited memory system may have to trade off capacity for generalization ability, such a trade-off has not been demonstrated in the past. We describe a simple model of memory that exhibits this trade-off and describe its performance in a variety of tasks.
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  35.  31
    Measuring Mental Entrenchment of Phrases with Perceptual Identification, Familiarity Ratings, and Corpus Frequency Statistics.Catherine Caldwell-Harris & Shimon Edelman - unknown
    Word recognition is the Petri dish of the cognitive sciences. The processes hypothesized to govern naming, identifying and evaluating words have shaped this field since its origin in the 1970s. Techniques to measure lexical processing are not just the back-bone of the typical experimental psychology laboratory, but are now routinely used by cognitive neuroscientists to study brain processing and increasingly by social and clinical psychologists (Eder, Hommel, and De Houwer 2007). Models developed to explain lexical processing have also aspired to (...)
    Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  36.  28
    Viewpoint Generalization in Face Recognition: The Role of Category-Speci C Processes.Shimon Edelman - unknown
    The statistical structure of a class of objects such as human faces can be exploited to recognize familiar faces from novel viewpoints and under variable illumination conditions. We present computational and psychophysical data concerning the extent to which class-based learning transfers or generalizes within the class of faces. We rst examine the computational prerequisite for generalization across views of novel faces, namely, the similarity of di erent faces to each other. We next describe two computational models which exploit the similarity (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  37.  18
    Vision Reanimated.Shimon Edelman - unknown
    Computer vision systems are, on most counts, poor performers, when compared to their biological counterparts. The reason for this may be that computer vision is handicapped by an unreasonable assumption regarding what it means to see, which became prevalent as the notions of intrinsic images and of representation by reconstruction took over the field in the late 1970’s. Learning from biological vision may help us to overcome this handicap.
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  38.  17
    The Neglected Universals: Learnability Constraints and Discourse Cues.Heidi Waterfall & Shimon Edelman - 2009 - Behavioral and Brain Sciences 32 (5):471-472.
    Converging findings from English, Mandarin, and other languages suggest that observed may be algorithmic. First, computational principles behind recently developed algorithms that acquire productive constructions from raw texts or transcribed child-directed speech impose family resemblance on learnable languages. Second, child-directed speech is particularly rich in statistical (and social) cues that facilitate learning of certain types of structures.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  39.  30
    A Swan, and Pike, and a Crawfish Walk Into a Bar.Shimon Edelman - 2008 - Journal of Experimental and Theoretical Ai 20:261-268.
    The three commentaries of Van Orden, Spivey and Anderson, and Dietrich (with Markman’s as a backdrop) form a tableau that reminds me of a fable by Ivan Andreevich Krylov (1769 - 1844), in which a swan, a pike, and a crawfish undertake jointly to move a cart laden with goods. What transpires then is not unexpected: the swan strives skyward, the pike pulls toward the river, and the crawfish scrambles backward. The call for papers for the present ecumenically minded special (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  40. Similarity-Based Viewspace Interpolation and the Categorization of 3D Objects.Shimon Edelman & Sharon Duvdevani-Bar - 1997 - In Proc. Edinburgh Workshop on Similarity and Categorization.
    Visual objects can be represented by their similarities to a small number of reference shapes or prototypes. This method yields low-dimensional (and therefore computationally tractable) representations, which support both the recognition of familiar shapes and the categorization of novel ones. In this note, we show how such representations can be used in a variety of tasks involving novel objects: viewpoint-invariant recognition, recovery of a canonical view, estimation of pose, and prediction of an arbitrary view. The unifying principle in all these (...)
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  41.  22
    Better Limited Systematicity in Hand Than Structural Descriptions in the Bush: A Reply to Hummel.Shimon Edelman & Nathan Intrator - 2003 - Cognitive Science 27 (2):331-332.
    No categories
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  42.  11
    Journal of The Cognitive Science Society.Robert L. Goldstone, John R. Anderson, Nick Chater, Andy Clark, Shimon Edelman, Kenneth Forbus, Dedre Gentner, Raymond W. Gibbs Jr, James Greeno & Robert A. Jacobs - 2004 - Cognitive Science 28 (3).
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  43.  7
    Regular Articles Learning to Divide the Labor: An Account of Deficits in Light and Heavy Verb Production 1 Jean K. Gordon, Gary S. Dell Semantic Grounding in Models of Analogy: An Environmental Approach 41.Michael Ramscar, Daniel Yarlett, Shimon Edelman, Nathan Intrator, Gergely Csibra, Szilvia Bıró, Orsolya Koós, György Gergely, Holk Cruse & Michael D. Lee - 2003 - Cognitive Science 27:945-948.
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  44.  18
    Tracks in the Mind: Differential Entrenchment of Common and Rare Liturgical and Everyday Multiword Phrases in Religious and Secular Hebrew Speakers.Catherine Caldwell-Harris & Shimon Edelman - unknown
    We tested the hypothesis that more frequent exposure to multiword phrases results in deeper entrenchment of their representations, by examining the performance of subjects of different religiosity in the recognition of briefly presented liturgical and secular phrases drawn from several frequency classes. Three of the sources were prayer texts that religious Jews are required to recite on a daily, weekly, and annual basis, respectively; two others were common and rare expressions encountered in the general secular Israeli culture. As expected, linear (...)
    No categories
    Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  45.  37
    An Evolved Model Agent by R. Beer.Shimon Edelman - unknown
    Beer ’s paper devotes much energy to buttressing the walls of Castle Dynamic and dredging its moat in the face of what some of its dwellers perceive as a besieging army chanting “no cognition without representation”. The divide is real, as attested by the contrast between titles such as “Intelligence without representation” and “In defense of representation”, to pick just one example from each side. It is, however, not too late for people from both sides of the moat to meet (...)
    Direct download  
     
    Export citation  
     
    Bookmark  
  46.  44
    A New Vision of Language.Shimon Edelman - unknown
    A metaphor that has dominated linguistics for the entire duration of its existence as a discipline views sentences as edifices consisting of Lego-like building blocks. It is assumed that each sentence is constructed (and, on the receiving end, parsed) ab novo, starting (ending) with atomic constituents, to logical semantic specifications, in a recursive process governed by a few precise algebraic rules. The assumptions underlying the Lego metaphor, as it is expressed in generative grammar theories, are: (1) perfect regularity of what (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  47.  9
    Brahe, Looking for Kepler.Shimon Edelman - 2000 - Behavioral and Brain Sciences 23 (4):538-540.
    Arbib, Érdi, and Szentágothai's book should be a required reading for any serious student of the brain. The scope and the accessibility of its presentation of the neurobiological data (especially the functional anatomy of select parts of the central nervous system) more than make up for the peculiarities of the theoretical stance it adopts.
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark  
  48.  90
    Complex Cells and Object Recognition.Shimon Edelman - unknown
    Nearest-neighbor correlation-based similarity computation in the space of outputs of complex-type receptive elds can support robust recognition of 3D objects. Our experiments with four collections of objects resulted in mean recognition rates between 84% and 94%, over a 40 40 range of viewpoints, centered on a stored canonical view and related to it by rotations in depth. This result has interesting implications for the design of a front end to an arti cial object recognition system, and for the understanding of (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  49.  57
    Evolution of Dynamic Coordination.Shimon Edelman & Erich D. Jarvis - unknown
    What insights does comparative biology provide for furthering scienti¿ c understanding of the evolution of dynamic coordination? Our discussions covered three major themes: (a) the fundamental unity in functional aspects of neurons, neural circuits, and neural computations across the animal kingdom; (b) brain organization –behavior relationships across animal taxa; and (c) the need for broadly comparative studies of the relationship of neural structures, neural functions, and behavioral coordination. Below we present an overview of neural machinery and computations that are shared (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  50.  51
    Evolution of Language Diversity: The Survival of the Fitness.Shimon Edelman - unknown
    We examined the role of fitness, commonly assumed without proof to be conferred by the mastery of language, in shaping the dynamics of language evolution. To that end, we introduced island migration (a concept borrowed from population genetics) into the shared lexicon model of communication (Nowak et al., 1999). The effect of fitness linear in language coherence was compared to a control condition of neutral drift. We found that in the neutral condition (no coherence-dependent fitness) even a small migration rate (...)
    Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark