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Topic: Connectionist

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	Connectionism
		Connectionists tend to avoid recurrent connections because little is understood about the general problem of training recurrent nets.
		The connectionist views mental processing as the dynamic and graded evolution of activity in a neural net, each unit's activation depending on the connection strengths and activity of its neighbors, according to the activation function.
		The complaint against connectionists is that while they may implement systems that exhibit systematicity, they will not have explained it unless it follows from their models as a nomic necessity.
	plato.stanford.edu /entries/connectionism (6671 words)

	Some Myths of Connectionism
		The discrepancy between the state of affairs in connectionist networks as compared to biological neural networks merely serves to further undermine the tenability of the claim that connectionist systems are biologically plausible.
		In most connectionist networks, the relationship between the signal sent down a connection and the influence of that connection (with the associated weighting) upon the receiving unit is fairly straightforward.
		So, connectionist might think of eschewing the lab for a little while and spending some time constructing arguments to support those claims which they consider to be axiomatic to their research program.
	www.ucs.louisiana.edu /~isb9112/dept/phil341/myths/myths.html (6773 words)

	The Connectionist Approach
		In a connectionist model, each unit receives “activation” from other units to which it is connected in response to the stimulation of these units.
		A connectionist network’s response to a stimulus generally involves successive activation of a number of nodes in the network.
		Thus the processes operating within connectionist networks can be assumed to correspond to neuronal, cognitive, or behavioral events based on the intuitions of the network’s designer.
	www.cnbc.cmu.edu /disordermodels/connectionism.htm (1188 words)

	20th WCP: Aristotle, Connectionism, and the Morally Excellent Brain
		What an Aristotelian theory of ethics and a connectionist theory of mind have in common is the assumption that the successful mind/brain has the disposition to behave appropriately in appropriate circumstances.
		We may conclude that since a connectionist system is capable of having concepts relevant to the achievement of its ends, ends the system is disposed to pursue under appropriate circumstances, then the brain, as connectionist system, has some of the abilities required of a system capable of moral excellence.
		As we shall see, connectionist systems are also capable of matching means to ends, of modifying their own behavioral output relative to the demands of a perceived situation.
	www.bu.edu /wcp/Papers/Cogn/CognDemo.htm (3441 words)

	PhilSci Archive - Are Connectionist Models Theories of Cognition?
		This paper explores the question of whether connectionist models of cognition should be considered to be scientific theories of the cognitive domain.
		It is argued that in traditional scientific theories, there is a fairly close connection between the theoretical (unobservable) entities postulated and the empirical observations accounted for.
		In connectionist models, however, hundreds of theoretical terms are postulated -- viz., nodes and connections -- that are far removed from the observable phenomena.
	philsci-archive.pitt.edu /archive/00000201 (125 words)

	HAYEK AND CONNECTIONISM
		Connectionists, however, are interested neither in the rule-bound, deliberative efforts of the novice, nor in the sort of static knowledge that comes packaged in the form of scientific theories.
		The designers of connectionist systems, in contrast, set out to model the fact that knowing how is an evolving capacity of the knowing subject and is such that the content of knowledge and the process of gaining knowledge are not clearly separable from each other.
		There is no storehouse of memories from the connectionist point of view; rather, the connectionist system 'remembers' only in the sense that its processing patterns are subject to change, being constantly and cumulatively affected by what has been experienced in the way of processing in the past.
	ontology.buffalo.edu /smith/articles/HAYEK.HTM (6319 words)

	Vrije Universiteit Brussel
		A multi-agent connectionist model is proposed that is capable of simulating these stereotype confirmation biases in group communication, as well as the effects of some moderating conditions.
		This paper discusses a recurrent connectionist network, simulating empirical phenomena usually explained by current dual-process approaches of attitudes, thereby focusing on the processing mechanisms that may underlie both central and peripheral routes of persuasion.
		Standard connectionist models of pattern completion like an auto-associator, typically fill in the activation of a missing feature with internal input from nodes that are connected to it.
	www.vub.ac.be /PESP/VanOverwalle.html (4500 words)

	Smith (1996) Abstract (Site not responding. Last check: 2007-10-08)
		In contrast to traditional symbolic theories, connectionist models require consideration of two levels: one involving many simple processing units that send activation signals over connections, and a higher level at which the representation of concepts (as distributed patterns of activation) and information processing, learning, and memory can be described.
		Connectionist models naturally offer many properties emphasized in existing social psychological theories: they can operate like schemas to fill in typical values for input information, reconstruct memories based on many sources of accessible knowledge rather than by retrieving static representations, operate with flexible and context-sensitive concepts, and compute by satisfying numerous constraints in parallel.
		The paper reviews critiques and open questions regarding connectionist models, and concludes that the contributions of our field, perhaps particularly to the understanding of cognition-motivation interactions, may be important for the future development of connectionist models that can integrate psychology as a whole.
	www.indiana.edu /~soccog/jpspconn.html (209 words)

	Connectionist Languages of Thought - Eric Lormand
		Connectionist opponents of the language-of-thought hypothesis have considered their most powerful weapon to be features of distributed symbols, or contentful patterns of activation of multiple nodes.
		As most connectionists agree, it is characteristic of connectionists models that use only local symbols (individual nodes), such as the interactive activation model of reading (see section 1.2).
		The state of activation of a connectionist node n at time t is, for example, a spatial part of the state of activity of n and another node n’ at t, and is a temporal part of the state of activation of n at t and t’.
	www-personal.umich.edu /~lormand/phil/cogsci/clot.htm (12805 words)

	Connectionist Content - Eric Lormand
		Although the connectionist puzzle for fine-grained theories is somewhat independent of the particular account adopted, it is necessary to have one on the table in order to describe the puzzle.
		Since simple propositions may serve as contents of connectionist nodes, and since such representations seem to be required by research programs which show some promise of yielding true theories of at least some cognitive phenomena, good methodology dictates that we should believe in simple propositions, if we want a fine-grained theory of content at all.
		Therefore, if connectionist networks are to fulfill their appointed task of helping to explain certain rationally evaluable mental processes--e.g., the "tacit inference" involved in perception--they must contain some units of reasoning, i.e., some propositional symbols.
	www-personal.umich.edu /~lormand/phil/cogsci/diss_ch2.htm (13103 words)

	Fodor and Pylshyn Refuted
		Fodor and Pylyshyn define connectionist systems as a large network of nodes that sum all of their input then and output some value according to a certain simple function.
		In the connectionist views, the associations between representations are also quite powerless except for the fact that their representations are distributed ones with a great deal of internal structure.
		Programming a connectionist network to change its size as necessary is an extremely challenging task at best, and perhaps even impossible to properly train at worst.
	www.msu.edu /user/marablek/fp.htm (10994 words)

	Dictionary of Philosophy of Mind - connectionism (Site not responding. Last check: 2007-10-08)
		Connectionist models can be classified by representational commitments in two categories; distributed and localist.
		Distributed representations are vectors in a representational state space, and are processed simultaneously by many nodes in a connectionist network.
		As well, it is thought that the only role for connectionist work is to provide a method for implementing a symbolicist system in a manner similar to the brain.
	www.artsci.wustl.edu /~philos/MindDict/connectionism.html (461 words)

	Connectionist Epistemology
		This research seeks to understand connectionist epistemology, for its applications in artificial intelligence, cognitive science and neuroscience.
		A proposed theoretical construct (the simulacrum) for connectionist models analogous to the calculus in symbolic models.
		We present a construct, called a simulacrum, which has a similar relation to connectionist knowledge representation as the calculus does to symbolic knowledge representation.
	www.cs.utk.edu /~mclennan/conn-epist.html (878 words)

	Robert M. French homepage
		These simulations show that that a “dual-network” connectionist model that incorporates both bottom-up (i.e., short-term memory) and top-down (i.e., long-term memory) processing is sufficient to account for the empirical results obtained with the infants.
		We hope that the ground-breaking work of these authors will naturally evolve towards broader-based distributed connectionist network models and related dynamical models of bilingual memory, capable of learning and being able to incorporate both the bottom-up and the top-down processing that we know to be in integral part of bilingual language processing.
		We use a combination of connectionist modeling and experimental testing of infants to show that the asymmetry can be reversed by an appropriate pre-selection and minor image modification of cat and dog exemplars used for familiarization.
	www.ulg.ac.be /cogsci/rfrench.html (10238 words)

	D. Mareschal
		Connectionist networks are particularly well suited for modelling development because they develop their own internal representations in response to environmental pressures.
		g., a connectionist autoencoder network or a 3-month-old infant) interact with the distibution of meaningful features in the environment to cause the observed patterns of development in children and infants.
		A connectionist account of interference effects in early infant memory and categorization in Proceedings of the nineteenth annual conference of the Cognitive Science Society (pp.
	www.psyc.bbk.ac.uk /people/academic/mareschal_d (1344 words)

	Linguistics 431/631: Connectionist Language Modeling (Site not responding. Last check: 2007-10-08)
		This course is an introduction to the connectionist modeling of language.
		Students will be expected to complete all exercises, so that they can compile them into their own self-created manual on connectionist modeling, which they can use later on in their career.
		For example, a student might decide to design a connectionist model of the acquisition of phonological patterns in L1 and L2 speakers, or one of semantic categorization.
	www2.hawaii.edu /~bergen/ling631 (497 words)

	Citations: Catastrophic interference in connectionist networks: The sequential learning problem - McCloskey, Cohen ... (Site not responding. Last check: 2007-10-08)
		The vast majority of connectionist networks suffer from this problem because of the highly distributed nature of their internal representations.
		In their article they present two examples in which the learning of a new piece of information in a network that is already trained, can seriously (catastrophically) interfere with the information that was....
		Although these studies did achieve some success in their goal of modelling cognitive processes, the algorithms described weren t evaluated on real world tasks nor on simpler problems that were related to real world tasks in some....
	citeseer.ist.psu.edu /context/11040/0 (2734 words)

	428/628: Connectionist Psycholinguistics
		Connectionist psycholinguistics involves using (artificial) 'neural' networks, which are inspired by brain architecture, to model empirical data on the acquisition and processing of language.
		We will furthermore discuss the broader implications of connectionist models of language, not only for psycholinguistics, but also for computational and linguistic perspectives on language.
		Christiansen has worked extensively with connectionist models of language and is currently working on a book (with Dr. Nick Chater, University of Warwick) outlining an integrated connectionist framework for understanding the evolution, acquisition and processing of language.
	instruct1.cit.cornell.edu /courses/psych428 (677 words)

	Connectionist Natural Language Processing (Site not responding. Last check: 2007-10-08)
		Since then my work has changed focus to concentrate on Connectionist Representations and in particular their capacity for Holistic Computation.
		Connectionist NLP is a young field, born of the connectionist revival in the 1980s.
		Connectionist systems for parsing, case-role assignment, script processing and machine translation have been developed, and work on connectionist representation techniques has given rise to connectionist methods for handling complex recursive structures.
	www.tardis.ed.ac.uk /~james/CNLP/cnlp.html (278 words)

	Professor Ron Sun
		A hybrid connectionist model Clarion has been developed, which combines both procedural knowledge and declarative knowledge in one framework.
		Within the framework, the following issues were also investigated: (1) The connectionist implementations of rules, logics, and schemas, and the variable binding problem in such implementations.
		A connectionist account was developed based on CONSYDERR, which extended the existing logic-based account and dealt better with the inexact, cumulative, and subjective nature of commonsense causal reasoning.
	www.cecs.missouri.edu /~rsun (3207 words)

	Connectionist Models of Cognition
		Connectionist Models of Cognition is a web-based textbook designed to introduce the key concepts in the area of neural networks.
		A background in connectionist theory is not required.
		The BrainWave connectionist simulator is embedded within the materials, allowing you to interact with the figures as you work through the exercises.
	www.itee.uq.edu.au /%7Ecogs2010/cmc/home.html (332 words)

	Professor Ron Sun
		The 1994 Bibliography on Connectionist Symbolic Integration (edited by Ron Sun, appeared in the book Computational Architectures Integrating Symbolic and Connectionist Processing, published by Kluwer).
		My research interest lies in the study and modeling of cognitive agents, especially in their abilities to learn, reason, and act in the real world.
		To capture such reasoning, I developed a hybrid connectionist architecture (named CONSYDERR) with both localist and distributed components, that unified rule-based and similarity-based processes and accounted for a variety of CSR patterns.
	www.cogsci.rpi.edu /~rsun (3392 words)

	Abstract for ``Connectionist Learning of Belief Networks'' (Site not responding. Last check: 2007-10-08)
		Connectionist learning procedures are presented for ``sigmoid'' and ``noisy-OR'' varieties of probabilistic belief networks.
		These networks have previously been seen primarily as a means of representing knowledge derived from experts.
		These networks have other advantages over Boltzmann machines in pattern classification and decision making applications, are naturally applicable to unsupervised learning problems, and provide a link between work on connectionist learning and work on the representation of expert knowledge.
	www.cs.toronto.edu /~radford/belief-net.abstract.html (219 words)

	Mother Nature vs. the Walking Encyclopedia
		Or as it is often put, a connectionist architecture can accomplish these special cognitive feats only by being a "mere implementation" of a "classical" symbol-manipulating architecture.
		For the fact is that connectionist models actually do surprising things, and if they didn't, they would not have sustained enough interest to warrant this volume.
		If it weren't for the actual computer implementations of connectionist systems, we would have, perhaps, the fervently expressed beliefs of a few visionaries who were sure that somehow, such an architecture could perform wonders, but visionaries with persuasive ideologies are a dime a dozen, and debates between visionaries are what lawyers rudely call pissing contests.
	ase.tufts.edu /cogstud/papers/motherna.htm (3031 words)

	Paul Smolensky \| JHU Cognitive Science Department
		Optimality Theory which brings general connectionist computational principles of optimization into the heart of the symbolic theory of universal grammar.
		The optimization that emerges is no longer inherently numerical: constraint strengths are encoded in a hierarchy of constraints, ranked from strongest to weakest; each constraint is stronger than all weaker constraints combined.
		Faculty, Connectionist Models Summer School; Carnegie-Mellon University, 1986, 1988; University of California, San Diego, 1990; University of Colorado, Boulder, 1993.
	www.cog.jhu.edu /faculty/smolensky (2518 words)

	A Connectionist model of Planning via Back-chaining Search (ResearchIndex) (Site not responding. Last check: 2007-10-08)
		Abstract: A connectionist model for emergent planning behavior is proposed.
		The model demonstrates that a simple planning schema, acting in concert with two general purpose cognitive functionalities, namely, episodic memory and perception, can solve a restricted class of planning problems by backchaining from the goal to the current state.
		2 A connectionist encoding of parameterized schemas and reacti..
	citeseer.ist.psu.edu /534990.html (499 words)

	connectionism preface2
		the probabilistic contrast model, and the connectionist model, is that the probabilistic contrast
		the connectionist model is also sensitive to the absolute frequency of presentation.
		In contrast, the connectionist model is sensitive to the absolute frequency of pairing of the
	www-rcf.usc.edu /~read/connectionism_preface2.html (6763 words)

	ECAI2000 Workshop. Symbolic-connectionist integration
		In recent years much attention has been paid to the integration of connectionist systems with symbol based techniques.
		The interest in developing connectionist architectures capable of dealing with these rich representations (as opposed to "flat" or vector-based representations) can be traced back to the end of the 80's.
		Whereas the purely connectionist ("connectionist-to-the-top") approach claims that complex symbol processing functionalities can be achieved via neural networks alone, the hybrid approach is premised on the complementarity of the two paradigms and aims at their synergistic combination in systems comprising both neural and symbolic components.
	www.dsi.unifi.it /~paolo/ECAI2000 (642 words)

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