Intelligence Without Representation: a Historical Perspective
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Behavior Trees in Robotics and AI
Michele Colledanchise and Petter Ogren¨ Behavior Trees in Robotics and AI An Introduction arXiv:1709.00084v4 [cs.RO] 3 Jun 2020 Contents 1 What are Behavior Trees? ....................................... 3 1.1 A Short History and Motivation of BTs . .4 1.2 What is wrong with FSMs? The Need for Reactiveness and Modularity . .5 1.3 Classical Formulation of BTs. .6 1.3.1 Execution Example of a BT . .9 1.3.2 Control Flow Nodes with Memory . 11 1.4 Creating a BT for Pac-Man from Scratch . 12 1.5 Creating a BT for a Mobile Manipulator Robot . 14 1.6 Use of BTs in Robotics and AI . 15 1.6.1 BTs in autonomous vehicles . 16 1.6.2 BTs in industrial robotics . 18 1.6.3 BTs in the Amazon Picking Challenge . 20 1.6.4 BTs inside the social robot JIBO . 21 2 How Behavior Trees Generalize and Relate to Earlier Ideas . 23 2.1 Finite State Machines . 23 2.1.1 Advantages and disadvantages . 24 2.2 Hierarchical Finite State Machines . 24 2.2.1 Advantages and disadvantages . 24 2.2.2 Creating a FSM that works like a BTs . 29 2.2.3 Creating a BT that works like a FSM . 32 2.3 Subsumption Architecture . 32 2.3.1 Advantages and disadvantages . 33 2.3.2 How BTs Generalize the Subsumption Architecture . 33 2.4 Teleo-Reactive programs . 33 2.4.1 Advantages and disadvantages . 34 2.4.2 How BTs Generalize Teleo-Reactive Programs . 35 2.5 Decision Trees . 35 2.5.1 Advantages and disadvantages . -
Warren Mcculloch and the British Cyberneticians
Warren McCulloch and the British cyberneticians Article (Accepted Version) Husbands, Phil and Holland, Owen (2012) Warren McCulloch and the British cyberneticians. Interdisciplinary Science Reviews, 37 (3). pp. 237-253. ISSN 0308-0188 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/id/eprint/43089/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the URL above for details on accessing the published version. Copyright and reuse: Sussex Research Online is a digital repository of the research output of the University. Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available. Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. http://sro.sussex.ac.uk Warren McCulloch and the British Cyberneticians1 Phil Husbands and Owen Holland Dept. Informatics, University of Sussex Abstract Warren McCulloch was a significant influence on a number of British cyberneticians, as some British pioneers in this area were on him. -
Kybernetik in Urbana
Kybernetik in Urbana Ein Gespräch zwischen Paul Weston, Jan Müggenburg und James Andrew Hutchinson1 Paul Ernest Weston was born on February 3rd 1935 in Garland, Maine. After stu- dying physics at Wesleyan University in Middletown (Connecticut), 1952 through 1956, Paul Weston came to the University of Illinois in summer 1956, receiving his M.S. in August 1958. The following autumn, as a graduate student of physics, he attended a seminar led by Heinz von Foerster under the promising title „Cyberne- tics“.2 In June 1959 Paul joins the newly founded Biological Computer Laboratory (BCL) as a half time research assistant employed by the Electrical Engineering Department. Through roughly 1962, Weston’s primary emphasis was upon simulation of the processes of perception, with work in neuron models and pattern recognition. Together with Murray Babcock, Weston was one of the most prominent creators of prototypes built at the BCL. Already in 1961 Weston becomes widely known as the inventor of the NumaRete, a parallel operated pattern recognition machine, which played an important role in the public perception of the BCL through out the fol- lowing years.3 After 1964 Weston continues his research at BCL on the basis of a full position as a research assistant and starts to focus on information processing, particularly inte- rested in problems associated with natural-language interaction with machine. As a member of the Committee for Cognitive Studies Weston is also increasingly interes- ted in the potentials of how the new information technologies could shape society. In June 1970 Weston receives his PhD for developing a new and more efficient data structure called CYLINDER.4 After the BCL was closed in 1975 Weston continued to work as a Research Associate at the Department of Electrical Engineering and the Coordinated Science Laboratory of the University of Illinois. -
1011 Neurons } 1014 Synapses the Cybernetics Group
History 329/SI 311/RCSSCI 360 Computers and the Internet: A global history Week 6: Computing and Cybernetics in the Soviet Union Today } Review } Cybernetics: minds, brains, and machines } Soviet computing and cybernetics } Soviet economic planning } Next time Review: SAGE } Origin: Whirlwind digital computer project, MIT } SAGE = Semi-Automatic Ground Environment } Computer-controlled air defense of lower 48 states } Networked over telephone lines } Duplexed (two computers for high reliability) } Tube-based central processors made by IBM } Magnetic core memory } First truly large software development } Served as a pattern for many subsequent military projects } Major factor in US and IBM dominance of commercial computer markets by late1950s Cybernetics: minds, brains, and machines Key figures } Norbert Wiener } cybernetics } Warren McCulloch & Walter Pitts } neural nets } John von Neumann } brain modeling, cellular automata, biological metaphors } Frank Rosenblatt } perceptrons The Cybernetics Group } Norbert Wiener, MIT } WWII anti-aircraft problems } Servo/organism analogies } “Behavior, Purpose, and Teleology” (1943) } Information as measurable quantity } Feedback: circular self-corrective cycles BEHAVIOR, PURPOSE AND TELEOLOGY 21 Examples of predictions of higher order are shooting with a sling or with a bow and arrow. Predictive behavior requires the discrimination of at least two coordinates, a temporal and at least one spatial axis. Prediction will be more effective and flexible, however, if the behaving object can respond to changes in more than one spatial coordinate. The sensory receptors of an organism, or the corresponding elements of a machine, may therefore limit the predictive behavior. Thus, a bloodhound follows a trail, that is, it does not show any predictive behavior in trailing, because a chemical, olfactory input reports only spatial information: distance, as indicated by intensity. -
Journal of Sociocybernetics
JOURNAL OF SOCIOCYBERNETICS _________________________________________________________________ Volume 3 Number 1 Spring/Summer 2002 Official Journal of the Research Committee on Sociocybernetics (RC51) of the International Sociological Association JOURNAL OF SOCIOCYBERNETICS www.unizar.es/sociocybernetics/ Editor Richard E. Lee Newsletter Cor Van Dijkum Felix Geyer Editorial Board Mike Byron Tessaleno Devezas Jorge González Bernd R. Hornung Chaime Marcuello Vessela Misheva Philip Nikolopoulos Bernard Scott Mike Terpstra ____________________________________________________________________________ The JOURNAL OF SOCIOCYBERNETICS (ISSN 1607-8667) is an electronic journal published biannually--Spring/Summer and Fall/Winter--by the Research Committee on Sociocybernetics of the International Sociological Association. MANUSCRIPT submissions should be sent electronically (in MSWord or Rich Text File format) to each of the editors: Richard E. Lee [email protected], Felix Geyer, [email protected], and Cor van Dijkum, [email protected]. In general, please follow the Chicago Manuel of Style; citations and bibliography should follow the current journal style (APA). Normally, articles should be original texts of no more than 6000 words, although longer articles will be considered in exceptional circumstances. The Journal looks for submissions that are innovative and apply principles of General Systems Theory and Cybernetics to the social sciences, broadly conceived. COPYRIGHT remains the property of authors. Permission to reprint must be obtained from the authors and the contents of JoS cannot be copied for commercial purposes. JoS does, however, reserve the right to future reproduction of articles in hard copy, portable document format (.pdf), or HTML editions of JoS. iii SOCIOCYBERNETICS traces its intellectual roots to the rise of a panoply of new approaches to scientific inquiry beginning in the 1940's. -
History of Robotics: Timeline
History of Robotics: Timeline This history of robotics is intertwined with the histories of technology, science and the basic principle of progress. Technology used in computing, electricity, even pneumatics and hydraulics can all be considered a part of the history of robotics. The timeline presented is therefore far from complete. Robotics currently represents one of mankind’s greatest accomplishments and is the single greatest attempt of mankind to produce an artificial, sentient being. It is only in recent years that manufacturers are making robotics increasingly available and attainable to the general public. The focus of this timeline is to provide the reader with a general overview of robotics (with a focus more on mobile robots) and to give an appreciation for the inventors and innovators in this field who have helped robotics to become what it is today. RobotShop Distribution Inc., 2008 www.robotshop.ca www.robotshop.us Greek Times Some historians affirm that Talos, a giant creature written about in ancient greek literature, was a creature (either a man or a bull) made of bronze, given by Zeus to Europa. [6] According to one version of the myths he was created in Sardinia by Hephaestus on Zeus' command, who gave him to the Cretan king Minos. In another version Talos came to Crete with Zeus to watch over his love Europa, and Minos received him as a gift from her. There are suppositions that his name Talos in the old Cretan language meant the "Sun" and that Zeus was known in Crete by the similar name of Zeus Tallaios. -
A Defense of Pure Connectionism
City University of New York (CUNY) CUNY Academic Works All Dissertations, Theses, and Capstone Projects Dissertations, Theses, and Capstone Projects 2-2019 A Defense of Pure Connectionism Alex B. Kiefer The Graduate Center, City University of New York How does access to this work benefit ou?y Let us know! More information about this work at: https://academicworks.cuny.edu/gc_etds/3036 Discover additional works at: https://academicworks.cuny.edu This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] A DEFENSE OF PURE CONNECTIONISM by ALEXANDER B. KIEFER A dissertation submitted to the Graduate Faculty in Philosophy in partial fulfillment of the requirements for the degree of Doctor of Philosophy, The City University of New York 2019 © 2019 ALEXANDER B. KIEFER All Rights Reserved ii A Defense of Pure Connectionism By Alexander B. Kiefer This manuscript has been read and accepted by the Graduate Faculty in Philosophy in satisfaction of the dissertation requirement for the degree of Doctor of Philosophy. _________________________ _________________________________________ 1/22/2019 Eric Mandelbaum Chair of Examining Committee _________________________ _________________________________________ 1/22/2019 Nickolas Pappas Executive Officer Supervisory Committee: David Rosenthal Jakob Hohwy Eric Mandelbaum THE CITY UNIVERSITY OF NEW YORK iii ABSTRACT A Defense of Pure Connectionism by Alexander B. Kiefer Advisor: David M. Rosenthal Connectionism is an approach to neural-networks-based cognitive modeling that encompasses the recent deep learning movement in artificial intelligence. It came of age in the 1980s, with its roots in cybernetics and earlier attempts to model the brain as a system of simple parallel processors. -
THE INTELLECTUAL ORIGINS of the Mcculloch
JHBS—WILEY RIGHT BATCH Top of ID Journal of the History of the Behavioral Sciences, Vol. 38(1), 3–25 Winter 2002 ᭧ 2002 John Wiley & Sons, Inc. (PHYSIO)LOGICAL CIRCUITS: THE INTELLECTUAL ORIGINS OF THE Base of 1st McCULLOCH–PITTS NEURAL NETWORKS line of ART TARA H. ABRAHAM This article examines the intellectual and institutional factors that contributed to the col- laboration of neuropsychiatrist Warren McCulloch and mathematician Walter Pitts on the logic of neural networks, which culminated in their 1943 publication, “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Historians and scientists alike often refer to the McCulloch–Pitts paper as a landmark event in the history of cybernetics, and funda- mental to the development of cognitive science and artificial intelligence. This article seeks to bring some historical context to the McCulloch–Pitts collaboration itself, namely, their intellectual and scientific orientations and backgrounds, the key concepts that contributed to their paper, and the institutional context in which their collaboration was made. Al- though they were almost a generation apart and had dissimilar scientific backgrounds, McCulloch and Pitts had similar intellectual concerns, simultaneously motivated by issues in philosophy, neurology, and mathematics. This article demonstrates how these issues converged and found resonance in their model of neural networks. By examining the intellectual backgrounds of McCulloch and Pitts as individuals, it will be shown that besides being an important event in the history of cybernetics proper, the McCulloch– Pitts collaboration was an important result of early twentieth-century efforts to apply mathematics to neurological phenomena. ᭧ 2002 John Wiley & Sons, Inc. -
Origins of the American Association for Artificial Intelligence
AI Magazine Volume 26 Number 4 (2006)(2005) (© AAAI) 25th Anniversary Issue The Origins of the American Association for Artificial Intelligence (AAAI) Raj Reddy ■ This article provides a historical background on how AAAI came into existence. It provides a ratio- nale for why we needed our own society. It pro- vides a list of the founding members of the com- munity that came together to establish AAAI. Starting a new society comes with a whole range of issues and problems: What will it be called? How will it be financed? Who will run the society? What kind of activities will it engage in? and so on. This article provides a brief description of the consider- ations that went into making the final choices. It also provides a description of the historic first AAAI conference and the people that made it happen. The Background and the Context hile the 1950s and 1960s were an ac- tive period for research in AI, there Wwere no organized mechanisms for the members of the community to get together and share ideas and accomplishments. By the early 1960s there were several active research groups in AI, including those at Carnegie Mel- lon University (CMU), the Massachusetts Insti- tute of Technology (MIT), Stanford University, Stanford Research Institute (later SRI Interna- tional), and a little later the University of Southern California Information Sciences Insti- tute (USC-ISI). My own involvement in AI began in 1963, when I joined Stanford as a graduate student working with John McCarthy. After completing my Ph.D. in 1966, I joined the faculty at Stan- ford as an assistant professor and stayed there until 1969 when I left to join Allen Newell and Herb Simon at Carnegie Mellon University Raj Reddy. -
What Is Systems Theory?
What is Systems Theory? Systems theory is an interdisciplinary theory about the nature of complex systems in nature, society, and science, and is a framework by which one can investigate and/or describe any group of objects that work together to produce some result. This could be a single organism, any organization or society, or any electro-mechanical or informational artifact. As a technical and general academic area of study it predominantly refers to the science of systems that resulted from Bertalanffy's General System Theory (GST), among others, in initiating what became a project of systems research and practice. Systems theoretical approaches were later appropriated in other fields, such as in the structural functionalist sociology of Talcott Parsons and Niklas Luhmann . Contents - 1 Overview - 2 History - 3 Developments in system theories - 3.1 General systems research and systems inquiry - 3.2 Cybernetics - 3.3 Complex adaptive systems - 4 Applications of system theories - 4.1 Living systems theory - 4.2 Organizational theory - 4.3 Software and computing - 4.4 Sociology and Sociocybernetics - 4.5 System dynamics - 4.6 Systems engineering - 4.7 Systems psychology - 5 See also - 6 References - 7 Further reading - 8 External links - 9 Organisations // Overview 1 / 20 What is Systems Theory? Margaret Mead was an influential figure in systems theory. Contemporary ideas from systems theory have grown with diversified areas, exemplified by the work of Béla H. Bánáthy, ecological systems with Howard T. Odum, Eugene Odum and Fritj of Capra , organizational theory and management with individuals such as Peter Senge , interdisciplinary study with areas like Human Resource Development from the work of Richard A. -
Analysis of Artificial Intelligence Hypothesis from the Perspective of Philosophy
2019 4th International Social Sciences and Education Conference (ISSEC 2019) Analysis of Artificial Intelligence Hypothesis from the Perspective of Philosophy Zhang Yanan Yinchuan University of Energy, Yinchuan, 750000, China Keywords: Artificial intelligence; Philosophy of artificial intelligence; Formal; Intentionality Abstract: Artificial intelligence is closely related to philosophy, algorithms in artificial intelligence are closely related to logic, intentionality of intelligent machines is closely related to philosophy of mind and so on. However, the beginners of the development of artificial intelligence are concerned about technical problems, and are weak in philosophical thinking. With the development of artificial intelligence, it is necessary to think deeply about its philosophical problems to clarify its philosophical basis and clear away the technical obstacles of the development of artificial intelligence, so as to be conducive to the development of artificial intelligence technology and promote the progress of philosophical research. 1. Introduction In 1950 Alan Turing opened his classic book Computing Machinery and Intelligence by asking: can machines think? But he did not think such questions were worth discussing, for it was difficult to define thinking precisely, so Turing proposed his imitation game, the Turing test[1]. At the heart of the Turing test is whether a computer can behave in a way indistinguishable from a human, the first time that humans have thought behavioristically about the intelligence of a robot. John McCarthy in 19556 for the first time to use “AI (Artificial Intelligence, or AI, for short)” concept, he thought that Human Intelligence, Human Intelligence) as Artificial Intelligence concept to determine the premise, the ultimate goal is to make the computer program control simulating Human ability to solve problems of Artificial Intelligence, was born a to study how to use the machine to simulate the emerging discipline of Human Intelligence. -
Connectionist Models of Cognition Michael S. C. Thomas and James L
Connectionist models of cognition Michael S. C. Thomas and James L. McClelland 1 1. Introduction In this chapter, we review computer models of cognition that have focused on the use of neural networks. These architectures were inspired by research into how computation works in the brain and subsequent work has produced models of cognition with a distinctive flavor. Processing is characterized by patterns of activation across simple processing units connected together into complex networks. Knowledge is stored in the strength of the connections between units. It is for this reason that this approach to understanding cognition has gained the name of connectionism. 2. Background Over the last twenty years, connectionist modeling has formed an influential approach to the computational study of cognition. It is distinguished by its appeal to principles of neural computation to inspire the primitives that are included in its cognitive level models. Also known as artificial neural network (ANN) or parallel distributed processing (PDP) models, connectionism has been applied to a diverse range of cognitive abilities, including models of memory, attention, perception, action, language, concept formation, and reasoning (see, e.g., Houghton, 2005). While many of these models seek to capture adult function, connectionism places an emphasis on learning internal representations. This has led to an increasing focus on developmental phenomena and the origins of knowledge. Although, at its heart, connectionism comprises a set of computational formalisms,