Paul Smolensky
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Synergetic Environments Form, Social Behavior, and Coordination
Synergetic Environments Form, Social Behavior, and Coordination “In the most general sense, computation is the process of storing, transmitting, and transforming information from one form to another” (Santa Fe Institute). ARCH 6307/4050/6050, IT IS 6010, ITCS 5010 Wednesdays 6:00pm-8:45pm, Storrs 255 School of Architecture, UNC Charlotte Prof Dr. Dimitrios Papanikolaou / [email protected] Office hours: Wednesdays 10am-12pm by appointment Office: Storrs 146 Premise The seminar critically reviews the evolution and design principles of systems of urban and territorial intelligence, from the ancient networks of optical telegraphy to today’s internet of things. Through discussions, we will examine technologies, systems, and mechanisms for turning information into decision and action in large scales; we will question the role of the physical environment, resource scarcity, and human behavior in shaping equilibrium conditions; we will investigate the role of data, modeling, and simulation in exploring dynamics of urban systems; and we will critically speculate where the design field of urban computing might be heading in the future. Objectives By the end of the course, students will develop a broad yet critical understanding of what urban intelligence is, how it can be constructed, and what limits it may reach, from a sociotechnical and a systemic perspective. Topics include: Theory and technologies of computation, information, communication, and human factors in relation to the built environment; systems theory; cybernetics; 1 ARCH 4050/6050 FALL 2017, SoA, UNC Charlotte urban dynamics; ecology; social cooperation; collective intelligence; game theory; mechanism design; as well as applications in mobility, resource allocation, sustainability, and energy. Method The course combines discussions, lectures, and workshops. -
University of Groningen Finding the Right Words Bíró, Tamás Sándor
University of Groningen Finding the right words Bíró, Tamás Sándor IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2006 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Bíró, T. S. (2006). Finding the right words: implementing optimality theory with simulated annealing. s.n. Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 29-09-2021 Bibliography Arto Anttila. Morphologically conditioned phonological alternations. Natural Language and Linguistic Theory, 20:1{42, 2002. Also: ROA-425. -
A View from Gradient Harmonic Grammar
Asymmetries in Long-Distance Dependencies: A View from Gradient Harmonic Grammar constituent class membership to a degree, and presupposes that instead of standard category symbols like [X], there are weighted category symbols like [αX] (where α ranges over the real numbers in Hyunjung Lee & Gereon M¨uller (Universit¨at Leipzig) [0,1]). Rules, filters, and other syntactic building blocks are given upper and lower threshold values WorkshoponLong-DistanceDependencies,HUBerlin October 4-5, 2018 of α between which they operate. 1. Introduction Note: This way, the concept of varying strength of syntactic categories (see Chomsky (2015) for a recent Claim: reappraisal) can be formally implemented in the grammar. Gradient Harmonic Grammar (Smolensky & Goldrick (2016)) offers a new perspective on how to derive three different types of asymmetries as they can be observed with long-distance dependencies Observation: in the world’s languages: So far, most of the work on GHG has been in phonology (e.g., Zimmermann (2017), Faust & Smo- • asymmetries between movement types lensky (2017), Kushnir (2018)); but cf. Smolensky (2017), M¨uller (2017b), Lee (2018) for syntactic applications. • asymmetries between types of moved items • asymmetries between types of local domain 1.3. Harmonic Serialism Background assumptions: Note: (i) Harmonic Grammar Harmonic serialism is a strictly derivational version of optimality theory. (ii) Gradient Representations (3) Harmonic serialism (McCarthy (2008), Heck & M¨uller (2013)): (iii) Harmonic Serialism a. GivensomeinputIi, the candidate set CSi = {Oi1,Oi2, ...Oin} is generated by applying at 1.1. Harmonic Grammar most one operation to Ii. Harmonic Grammar (Smolensky & Legendre (2006), Pater (2016)): A version of optimality theory b. -
8418B0e55972ecac157afb730f8
Baltic Journal of Economic Studies Vol. 4, No. 2, 2018 DOI: https://doi.org/10.30525/2256-0742/2018-4-2-254-260 ANALYTIC OVERLOOK OF THE METHODOLOGY OF SYNERGETICS IN POSTNONCLASSICAL SCIENCE Viktor Yakimtsov1 Ukrainian National Forestry University, Ukraine Abstract. Purpose. This article reveals the main definitions of synergetics and methods that are being used in synergetic research. The differences-characteristics of classical, nonclassical, and postnonclassical science and their schematic illustration are described. There are criteria, by which the main methodological principles of synergetics are being chosen. The reasons that have caused an appearance of synergetics and its methodological apparatus and the framework of this apparatus are considered. The special aspects of nonlinearity of complicated systems, in our opinion, include the economic ones. Methodology. Such foreign and domestic scientists as Wiener N. (2003), Thom R. (1975, 1996), Prigogine I., Stengers I. (1986), Zang V.B. (1999), and Arnold V. (2004) have used methodological apparatus of synergetics in modern science. Methodologically synergetics is open for those new conceptions that are being formed in certain disciplines. Methodological principles of synergetics that cause the “colostral” principles are nonlinearity, nonclosure, and instability. The main principle – the rule of nonlinearity is a contravention of the principle of the super offer in the certain phenomenon (process): the result of adding the impacts on the system is not the adding these impacts’ results. The causes’ results cannot be added. This means that the result of adding the causes does not equal to the union of causes’ results. Results. For the synergy concept, the idea is typical that we see everything at once: the whole and its parts. -
Generalized Alignment John J
University of Massachusetts Amherst ScholarWorks@UMass Amherst Linguistics Department Faculty Publication Series Linguistics January 1993 Generalized alignment John J. McCarthy University of Massachusetts, Amherst, [email protected] Alan Prince Follow this and additional works at: https://scholarworks.umass.edu/linguist_faculty_pubs Part of the Morphology Commons, Near Eastern Languages and Societies Commons, and the Phonetics and Phonology Commons Recommended Citation McCarthy, John J. and Prince, Alan, "Generalized alignment" (1993). Yearbook of Morphology. 12. Retrieved from https://scholarworks.umass.edu/linguist_faculty_pubs/12 This Article is brought to you for free and open access by the Linguistics at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Linguistics Department Faculty Publication Series by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. Generalized Alignment* John J. McCarthy Alan S. Prince University of Massachusetts, Amherst Rutgers University §1. Introduction Overt or covert reference to the edges of constituents is a commonplace throughout phonology and morphology. Some examples include: •In English, Garawa, Indonesian and a number of other languages, the normal right-to-left alternation of stress is interrupted word-initially: (1) Initial Secondary Stress in English (Tàta)ma(góuchee) *Ta(tàma)(góuchee) (Lùxi)pa(lílla) *Lu(xìpa)(lílla) As the foot-brackets ( ) indicate, the favored outcome is one in which -
Harmonic Grammar with Linear Programming
To appear in Phonology 27(1):1–41 February 18, 2010 Harmonic grammar with linear programming: From linear systems to linguistic typology∗ Christopher Potts Joe Pater Stanford University UMass Amherst Karen Jesney Rajesh Bhatt UMass Amherst UMass Amherst Michael Becker Harvard University Abstract Harmonic Grammar (HG) is a model of linguistic constraint interac- tion in which well-formedness is calculated in terms of the sum of weighted constraint violations. We show how linear programming algorithms can be used to determine whether there is a weighting for a set of constraints that fits a set of linguistic data. The associated software package OT-Help provides a practical tool for studying large and complex linguistic systems in the HG framework and comparing the results with those of OT. We first describe the translation from harmonic grammars to systems solvable by linear programming algorithms. We then develop an HG analysis of ATR harmony in Lango that is, we argue, superior to the existing OT and rule-based treatments. We further highlight the usefulness of OT-Help, and the analytic power of HG, with a set of studies of the predictions HG makes for phonological typology. Keywords: Harmonic Grammar, Optimality Theory, linear programming, typology, Lango, ATR harmony, positional markedness, positional faithfulness 1 Introduction We examine a model of grammar that is identical to the standard version of Optimality Theory (OT: Prince & Smolensky 1993/2004), except that the optimal Our thanks to Ash Asudeh, Tim Beechey, Maitine Bergonioux, Paul Boersma, John Colby, Kathryn ∗ Flack, Edward Flemming, Bob Frank, John Goldmsith, Maria Gouskova, Bruce Hayes, René Kager, Shigeto Kawahara, John Kingston, John McCarthy, Andrew McKenzie, Ramgopal Mettu, Alan Prince, Kathryn Pruitt, Jason Riggle, Jim Smith, and Paul Smolensky, and other participants in conferences and courses where this material was presented. -
Ranking and Necessity
Ranking and Necessity Part I: The Fusional Reduction Algorithm ● 12-16-2005 ● Adrian Brasoveanu and Alan Prince Department of Linguistics Rutgers Center for Cognitive Science Rutgers University, New Brunswick ABSTRACT Understanding a linguistic theory within OT requires an exact characterization of the ranking conditions necessitated by data. We describe (Part I) and justify (Part II) an algorithm which calculates the necessary and sufficient ranking conditions inherent in any collection of candidates and presents them in a maximally concise and informative way. The algorithm, stemming from the original proposal of Brasoveanu 2003, develops in the setting of the fusional ERC theory of Prince 2002. ACKNOWLEDGMENTS The authors, whose names are arranged alphabetically, would like to thank Jane Grimshaw, Naz Merchant, Paul Smolensky, and Bruce Tesar for useful discussion; and, for helpful comments, audiences at the Rutgers Optimality Research Group (April 2004, Nov. 2005), HUMDRUM (May 2004), and the LSA 2005 Summer Institute. For support during aspects of the investigation, we thank the John Simon Guggenheim Memorial Foundation, the National Science Foundation (Grant No. BCS-0083101), and the National Institutes of Health (NRSA Training Grant No. 1-T32-MH-19975-05). The opinions, findings, conclusions, and recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or of the National Institutes of Health. The authors also claim responsibility for any errors, omissions, misprisions, or infelicities that may have crept into the text. Ranking and Necessity Part I 1. Beyond the Sufficient………………………………………………………………..3 2. The Consequences of Comparison………………………………………………..6 2.1 The Elementary Ranking Condition……………………………………..6 2.2 Informativeness……………………………………………………………9 2.3 ERCs and Consequences………………………………………………12 2.4 Remark on the Logical Background…………………………………...23 3. -
Generative Linguistics and Neural Networks at 60: Foundation, Friction, and Fusion*
Generative linguistics and neural networks at 60: foundation, friction, and fusion* Joe Pater, University of Massachusetts Amherst October 3, 2018. Abstract. The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. This paper traces the development of these two approaches to cognitive science, from their largely autonomous early development in their first thirty years, through their collision in the 1980s around the past tense debate (Rumelhart and McClelland 1986, Pinker and Prince 1988), and their integration in much subsequent work up to the present. Although this integration has produced a considerable body of results, the continued general gulf between these two lines of research is likely impeding progress in both: on learning in generative linguistics, and on the representation of language in neural modeling. The paper concludes with a brief argument that generative linguistics is unlikely to fulfill its promise of accounting for language learning if it continues to maintain its distance from neural and statistical approaches to learning. 1. Introduction At the beginning of 1957, two men nearing their 29th birthdays published work that laid the foundation for two radically different approaches to cognitive science. One of these men, Noam Chomsky, continues to contribute sixty years later to the field that he founded, generative linguistics. The book he published in 1957, Syntactic Structures, has been ranked as the most influential work in cognitive science from the 20th century.1 The other one, Frank Rosenblatt, had by the late 1960s largely moved on from his research on perceptrons – now called neural networks – and died tragically young in 1971. -
History of Cybernetics - R
SYSTEMS SCIENCE AND CYBERNETICS – Vol. III - History of Cybernetics - R. Vallee HISTORY OF CYBERNETICS R. Vallée Université Paris-Nord, France Keywords: Autopoiesis, cybernetics, entropy, feedback, information, noise, observation, variety. Contents 1. Origins of Cybernetics 1.1 Contemporary Initiators 1.2 Past Contributors 2. Basic Concepts 2.1 Foundations 2.1.1.Retroaction 2.1.2.Information 2.2 Other Important Concepts 2.2.1.Variety 2.2.2.Observers 2.2.3.Epistemology and Praxiology 2.2.4.Isomorphism and Multidisciplinarity 3. Links with Other Theories 4. Future of Cybernetics Appendix Glossary Bibliography Biographical Sketch Summary The most important initiator of cybernetics was Norbert Wiener (l894–1964) with his book “Cybernetics or Control and Communication in the Animal and the Machine”. The contribution of Warren S. McCulloch (1898–1969) may be compared to that of Wiener. Cybernetics UNESCOhas also had precursors such as– A. M.EOLSS Ampère who introduced the word cybernétique as well as B. Trentowski who did the same in Polish. H. Schmidt, S. Odobleja in the 1930s, and P. Postelnicu in the early 1940s recognized the general importance of the idea of negative feedback. SAMPLE CHAPTERS The basic concepts of cybernetics are negative feedback and information. A famous example of negative feedback is given by Watt’s governor, the purpose of which is to maintain the speed of the wheel of a steam engine, at a given value, despite perturbations. The theory of information, mainly due to Claude E. Shannon, gives a measure of the unexpectedness of a message carried by a signal. Other traits of cybernetics must be noted, such as the “principle of requisite variety” introduced by W. -
What Is Optimality Theory? John J
University of Massachusetts Amherst ScholarWorks@UMass Amherst Linguistics Department Faculty Publication Series Linguistics January 2007 What is Optimality Theory? John J. McCarthy University of Massachusetts, Amherst, [email protected] Follow this and additional works at: https://scholarworks.umass.edu/linguist_faculty_pubs Part of the Morphology Commons, Near Eastern Languages and Societies Commons, and the Phonetics and Phonology Commons Recommended Citation McCarthy, John J., "What is Optimality Theory?" (2007). Language and Linguistics Compass. 93. Retrieved from https://scholarworks.umass.edu/linguist_faculty_pubs/93 This Article is brought to you for free and open access by the Linguistics at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Linguistics Department Faculty Publication Series by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. 1 What is Optimality Theory?1 John J. McCarthy University of Massachusetts Amherst Abstract. Optimality Theory is a general model of how grammars are structured. This article surveys the motivations for OT, its core principles, and the basics of analysis. It also addresses some frequently asked questions about this theory and offers suggestions for further reading. 1. Introduction In 1991, Alan Prince and Paul Smolensky began presenting their work on a new approach to language. By 1993, this new approach had a name — Optimality Theory — and it became known through their widely-circulated manuscript Optimality Theory: Constraint Interaction in Generative Grammar (hereafter, Prince and Smolensky (2004)). The impact of this work on the field of phonology was extensive and immediate; since 1993, it has also stimulated important research in syntax, semantics, sociolinguistics, historical linguistics, and other areas. -
Synergetics - Hermann Haken
SYSTEMS SCIENCE AND CYBERNETICS – Vol. I - System Theories: Synergetics - Hermann Haken SYSTEM THEORIES: SYNERGETICS Hermann Haken Institute for Theoretical Physics 1, Center of Synergetics,University of Stuttgart, D- 70550 Stuttgart. Keywords: Self-organization, complex systems, instability, order parameter, slaving principle, control parameter, structure, spatial structure, temporal structure, symmetry breaking, fluctuations, chaos, laser, fluids, chemical patterns, pattern recognition, medicine, psychology, evolution, information, mathematics, physics, economy, humanities, open systems Contents 1. Review of Subject Articles 2. Definition of Synergetics 3. Goals and General Approaches 4. Some Typical Examples 4.1 The Laser 4.2 The Convection Instability of Fluid Dynamics 4.3 An Example from Sociology and Linguistics 5. Basic Concepts 6. Applications to Science 6.1 Physics 6.2 Chemistry 6.3 Mechanical Engineering 6.4 Electrical Engineering 6.5 Biology 6.6 Psychology 7. Applications to Technology 7.1 Computer Science 7.2 Informatics 7.3 Telecommunication 8. Applications to Humanities 8.1 EconomyUNESCO – EOLSS 8.2 Sociology 8.3 Linguistics 8.4 Culture Including Art and Literature 8.5 Philosophy SAMPLE CHAPTERS 8.6 Epistemology 9. Mathematical Tools 10. Relations to Other Approaches Glossary Bibliography Biographical Sketch Summary ©Encyclopedia of Life Support Systems (EOLSS) SYSTEMS SCIENCE AND CYBERNETICS – Vol. I - System Theories: Synergetics - Hermann Haken S. has links to many fields of the natural sciences, to technology and to the humanities. The outstanding feature of S. is its goal to unearth common features in the macroscopic behavior of a great variety of otherwise quite different systems. As this article witnesses, this goal has been achieved by means of central concepts, such as instability, order parameters and the slaving principle. -
Learning-Theoretic Linguistics: Some Examples from Phonology
Learning-Theoretic Linguistics: Some Examples from Phonology Bruce Hayes Department of Linguistics UCLA Relation of this talk to this session I’m not an expert on PDP at all! Inviting me here was quite a stretch. Common theme: learning about language through computational modeling. August 13, 2010 Hayes, Learning-theoretic linguistics 2 Some PDP models Letter perception McClelland and Rumelhart (1981), Rumelhart and McClelland (1982) Word recognition and naming Seidenberg, and McClelland (1989) Inflectional morphology Rumelhart and McClelland (1986) Speech perception McClelland and Elman (1986) Phonetic categories Vallabha et al. (2007) August 13, 2010 Hayes, Learning-theoretic linguistics 3 Linguistics in cognitive science . We’re externally famous for taking hard-line nativist views. As we view ourselves: obsession with language data and its patterning. August 13, 2010 Hayes, Learning-theoretic linguistics 4 A bit of generative linguistics The logical problem of language acquisition is at the core of linguistic theory (see, e.g. Chomsky 1965, Ch. 1) Premise: language acquisition is an extraordinary feat Proposed explanation: Universal Grammar + learning mechanisms August 13, 2010 Hayes, Learning-theoretic linguistics 5 Kinds of UG Hard UG: Grammatical principles in the genome Soft UG: Aspects of language shaped by human nature, e.g. phonetically-grounded phonology (e.g. Hayes, Kirchner and Steriade 2004) August 13, 2010 Hayes, Learning-theoretic linguistics 6 The modeling program for linguistic theory Learning model – perhaps