Much Has Been Written About the Turing Test in the Last Few Years, Some of It
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Lessons from a Restricted Turing Test
Lessons from a Restricted Turing Test Stuart M. Shieber Aiken Computation Laboratory Division of Applied Sciences Harvard University March 28, 1994 (Revision 6) Abstract We report on the recent Loebner prize competition inspired by Turing’s test of intelligent behavior. The presentation covers the structure of the competition and the outcome of its first instantiation in an actual event, and an analysis of the purpose, design, and appropriateness of such a competition. We argue that the competition has no clear purpose, that its design prevents any useful outcome, and that such a competition is inappropriate given the current level of technology. We then speculate as to suitable alternatives to the Loebner prize. arXiv:cmp-lg/9404002v1 4 Apr 1994 This paper is to appear in Communications of the Association for Comput- ing Machinery, and is available from the Center for Research in Computing Technology, Harvard University, as Technical Report TR-19-92 and from the Computation and Language e-print server as cmp-lg/9404002. The Turing Test and the Loebner Prize The English logician and mathematician Alan Turing, in an attempt to develop a working definition of intelligence free of the difficulties and philosophical pitfalls of defining exactly what constitutes the mental process of intelligent reasoning, devised a test, instead, of intelligent behavior. The idea, codified in his cel- ebrated 1950 paper “Computing Machinery and Intelligence” (Turing, 1950), was specified as an “imitation game” in which a judge attempts to distinguish which of two agents is a human and which a computer imitating human re- sponses by engaging each in a wide-ranging conversation of any topic and tenor. -
I V Anthropomorphic Attachments in U.S. Literature, Robotics, And
Anthropomorphic Attachments in U.S. Literature, Robotics, and Artificial Intelligence by Jennifer S. Rhee Program in Literature Duke University Date:_______________________ Approved: ___________________________ Kenneth Surin, Supervisor ___________________________ Mark Hansen ___________________________ Michael Hardt ___________________________ Katherine Hayles ___________________________ Timothy Lenoir Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Literature in the Graduate School of Duke University 2010 i v ABSTRACT Anthropomorphic Attachments in U.S. Literature, Robotics, and Artificial Intelligence by Jennifer S. Rhee Program in Literature Duke University Date:_______________________ Approved: ___________________________ Kenneth Surin, Supervisor ___________________________ Mark Hansen ___________________________ Michael Hardt ___________________________ Katherine Hayles ___________________________ Timothy Lenoir An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Literature in the Graduate School of Duke University 2010 Copyright by Jennifer S. Rhee 2010 Abstract “Anthropomorphic Attachments” undertakes an examination of the human as a highly nebulous, fluid, multiple, and often contradictory concept, one that cannot be approached directly or in isolation, but only in its constitutive relationality with the world. Rather than trying to find a way outside of the dualism between human and not- human, -
Philosophy of Artificial Intelligence: a Course Outline
Teaching Philosophy 9:2, June 1986 103 Philosophy of Artificial Intelligence: A Course Outline WILLIAM J. RAPAPORT State University ofNew York, Buffalo In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY· Fredonia, after retuming there from a year's leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computer-science majors, about a third had no <;omputer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the Philosophy Department's AI-related courses, such as logic, philosophy of mind, and epistemology, and that several computer science students have added philosophy as a second major.) This article describes that course, provides material for use in such a course, and offers a bibliography of relevant articles in the AI, cognitive science, and philosophical literature. Course Organization and Texts My original intention, inspired in part by Moulton and Voytek 1980, was to spend the first half of the semester discussing working AI programs, in order to get the students excited about what computers could do, using the first edition of Patrick Henry Winston's Artificial Intelligence (Winston 1977) as the text. During the second half of the semester, my plan was to discuss Hubert L. Dreyfus's What Computers Can't Do (Dreyfus 1979), as a sort of antidote and source of philosophical reflection. While I still think that this might have been a good course, I chose instead to use lohn Haugeland's anthology, Mind Design (Haugeland 1981), for the philosophical half of the course, since it offers a wider-and fairer-spectrum ofphilosophical essays, besides including the most important section ofDreyfus's book. -
A Imitation Learning: a Survey of Learning Methods
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by BCU Open Access A Imitation Learning: A Survey of Learning Methods Ahmed Hussein, School of Computing Science and Digital Media, Robert Gordon University Mohamed Medhat Gaber, School of Computing and Digital Technology, Birmingham City University Eyad Elyan , School of Computing Science and Digital Media, Robert Gordon University Chrisina Jayne , School of Computing Science and Digital Media, Robert Gordon University Imitation learning techniques aim to mimic human behavior in a given task. An agent (a learning machine) is trained to perform a task from demonstrations by learning a mapping between observations and actions. The idea of teaching by imitation has been around for many years, however, the field is gaining attention recently due to advances in computing and sensing as well as rising demand for intelligent applications. The paradigm of learning by imitation is gaining popularity because it facilitates teaching complex tasks with minimal expert knowledge of the tasks. Generic imitation learning methods could potentially reduce the problem of teaching a task to that of providing demonstrations; without the need for explicit programming or designing reward functions specific to the task. Modern sensors are able to collect and transmit high volumes of data rapidly, and processors with high computational power allow fast processing that maps the sensory data to actions in a timely manner. This opens the door for many potential AI applications that require real-time perception and reaction such as humanoid robots, self-driving vehicles, human computer interaction and computer games to name a few. -
Mental States in Animals: Cognitive Ethology Jacques Vauclair
Mental states in animals: cognitive ethology Jacques Vauclair This artHe addresses the quegtion of mentaJ states in animak as viewed in ‘cognitive ethology”. In effect, thk field of research aims at studying naturally occurring behaviours such as food caching, individual recognition, imitation, tool use and communication in wild animals, in order to seek for evidence of mental experiences, self-aw&&reness and intentional@. Cognitive ethologists use some philosophical cencepts (e.g., the ‘intentional stance’) to carry out their programme of the investigation of natural behaviours. A comparison between cognitive ethology and other approaches to the investigation of cognitive processes in animals (e.g., experimental animal psychology) helps to point out the strengths and weaknesses of cognitive ethology. Moreover, laboratory attempts to analyse experimentally Mentional behaviours such as deception, the relationship between seeing and knowing, as well as the ability of animals to monitor their own states of knowing, suggest that cognitive ethology could benefit significantly from the conceptual frameworks and methods of animal cognitive psychology. Both disciplines could, in fact, co&ribute to the understanding of which cognitive abilities are evolutionary adaptations. T he term ‘cognirive ethology’ (CE) was comed by that it advances a purposive or Intentional interpretation Griffin in The Question ofAnimd Au~aarmess’ and later de- for activities which are a mixture of some fixed genetically veloped in other publications’ ‘_ Although Griffin‘s IS’6 transmitred elements with more hexible behaviour?. book was first a strong (and certainly salutary) reacrion (Cognitive ethologists USC conceptual frameworks against the inhibitions imposed by strict behaviourism in provided by philosophers (such as rhe ‘intentional stance’)“. -
Nonverbal Imitation Skills in Children with Specific Language Delay
City Research Online City, University of London Institutional Repository Citation: Dohmen, A., Chiat, S. and Roy, P. (2013). Nonverbal imitation skills in children with specific language delay. Research in Developmental Disabilities, 34(10), pp. 3288-3300. doi: 10.1016/j.ridd.2013.06.004 This is the unspecified version of the paper. This version of the publication may differ from the final published version. Permanent repository link: http://openaccess.city.ac.uk/3352/ Link to published version: http://dx.doi.org/10.1016/j.ridd.2013.06.004 Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. City Research Online: http://openaccess.city.ac.uk/ [email protected] Full title: Nonverbal imitation skills in children with specific language delay Name and affiliations of authors Andrea Dohmen¹˒², Shula Chiat², and Penny Roy² ¹Department of Experimental Psychology, University of Oxford, 9 South Parks Road, Oxford OX1 3UD, UK ²Language and Communication Science Division, City University London, Northampton Square EC1V 0HB London, UK Corresponding author Andrea Dohmen University of Oxford / Department of Experimental Psychology 9 South Parks Road Oxford OX1 3UD, UK Email: [email protected] Telephone: 0044/1865/271334 2 Nonverbal imitation skills in children with specific language delay Abstract Research in children with language problems has focussed on verbal deficits, and we have less understanding of children‟s deficits with nonverbal sociocognitive skills which have been proposed to be important for language acquisition. -
Turing Test Does Not Work in Theory but in Practice
Int'l Conf. Artificial Intelligence | ICAI'15 | 433 Turing test does not work in theory but in practice Pertti Saariluoma1 and Matthias Rauterberg2 1Information Technology, University of Jyväskylä, Jyväskylä, Finland 2Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands Abstract - The Turing test is considered one of the most im- Essentially, the Turing test is an imitation game. Like any portant thought experiments in the history of AI. It is argued good experiment, it has two conditions. In the case of control that the test shows how people think like computers, but is this conditions, it is assumed that there is an opaque screen. On actually true? In this paper, we discuss an entirely new per- one side of the screen is an interrogator whose task is to ask spective. Scientific languages have their foundational limita- questions and assess the nature of the answers. On the other tions, for example, in their power of expression. It is thus pos- side, there are two people, A and B. The task of A and B is to sible to discuss the limitations of formal concepts and theory answer the questions, and the task of the interrogator is to languages. In order to represent real world phenomena in guess who has given the answer. In the case of experimental formal concepts, formal symbols must be given semantics and conditions, B is replaced by a machine (computer) and again, information contents; that is, they must be given an interpreta- the interrogator must decide whether it was the human or the tion. They key argument is that it is not possible to express machine who answered the questions. -
THE TURING TEST RELIES on a MISTAKE ABOUT the BRAIN For
THE TURING TEST RELIES ON A MISTAKE ABOUT THE BRAIN K. L. KIRKPATRICK Abstract. There has been a long controversy about how to define and study intel- ligence in machines and whether machine intelligence is possible. In fact, both the Turing Test and the most important objection to it (called variously the Shannon- McCarthy, Blockhead, and Chinese Room arguments) are based on a mistake that Turing made about the brain in his 1948 paper \Intelligent Machinery," a paper that he never published but whose main assumption got embedded in his famous 1950 paper and the celebrated Imitation Game. In this paper I will show how the mistake is a false dichotomy and how it should be fixed, to provide a solid foundation for a new understanding of the brain and a new approach to artificial intelligence. In the process, I make an analogy between the brain and the ribosome, machines that translate information into action, and through this analogy I demonstrate how it is possible to go beyond the purely information-processing paradigm of computing and to derive meaning from syntax. For decades, the metaphor of the brain as an information processor has dominated both neuroscience and artificial intelligence research and allowed the fruitful appli- cations of Turing's computation theory and Shannon's information theory in both fields. But this metaphor may be leading us astray, because of its limitations and the deficiencies in our understanding of the brain and AI. In this paper I will present a new metaphor to consider, of the brain as both an information processor and a producer of physical effects. -
Deep Reinforcement Learning Via Imitation Learning
Deep Reinforcement Learning via Imitation Learning Sergey Levine perception Action (run away) action sensorimotor loop Action (run away) End-to-end vision standard features mid-level features classifier computer (e.g. HOG) (e.g. DPM) (e.g. SVM) vision Felzenszwalb ‘08 deep learning Krizhevsky ‘12 End-to-end control standard state low-level modeling & motion motor observations estimation controller robotic prediction planning torques control (e.g. vision) (e.g. PD) deep motor sensorimotor observations torques learning indirect supervision actions have consequences Contents Imitation learning Imitation without a human Research frontiers Terminology & notation 1. run away 2. ignore 3. pet Terminology & notation 1. run away 2. ignore 3. pet Terminology & notation 1. run away 2. ignore 3. pet a bit of history… управление Lev Pontryagin Richard Bellman Contents Imitation learning Imitation without a human Research frontiers Imitation Learning training supervised data learning Images: Bojarski et al. ‘16, NVIDIA Does it work? No! Does it work? Yes! Video: Bojarski et al. ‘16, NVIDIA Why did that work? Bojarski et al. ‘16, NVIDIA Can we make it work more often? cost stability Learning from a stabilizing controller (more on this later) Can we make it work more often? Can we make it work more often? DAgger: Dataset Aggregation Ross et al. ‘11 DAgger Example Ross et al. ‘11 What’s the problem? Ross et al. ‘11 Imitation learning: recap training supervised data learning • Usually (but not always) insufficient by itself – Distribution mismatch problem • Sometimes works well – Hacks (e.g. left/right images) – Samples from a stable trajectory distribution – Add more on-policy data, e.g. -
Summer, 1974 Number 4
newstetten Iouusiana psyctuatic \ssociatuon A district branch of the American Psychiatric Association Robert L. Newman, Jr., M.D., Editor DISTRICT BRANCH Mary Coyle, Assistant Editor Volume 12 Summer, 1974 Number 4 CHAPTER OFFICERS ELECTED New officers have been elected by the four LPA chapters to serve during 197 4-7 5. George Bishop is President of the Baton Rouge Psychiatric Society, with Ray Manson as Vice President and Eugene James Hill as Secretary-Treasurer. Serving a second term as President of the New Orleans Area Psychiatric Association is Al Koy, and President-Elect is Al Olinde. Charles Steck is Secretary, Lindsay Graham is Treasurer, and the two Councillors are Ernie Svenson and Walter Prickett, President of the North Louisiana Chapter is Fred Marceau, with John Richie as President-Elect and Edward Leatherman as Secretary. Sidney Dupuy will head the Acadiana Psychiatric Association. The names of other officers had not been received when the NEWSLETTER went to press. Robert G. Heath, M.D. William M. Easson, M.D. HEATH RECEIVES LPA FALL MEETING LSU SEATS NEW CHAIRMAN FROMM-REICHMANN AWARD Dick Brunstetter and Remi Gonzalez Dr. William M. Easson assumed his are making plans now for the LPA Fall duties June 3, 1974 as Professor and Dr. Robert G. Heath, Professor and Meeting, tentatively scheduled for Sep- Chairman of the Department of Psychia- Chairman of the Department of Psychia- tember 13-14 in New Orleans. try and Biobehavioral Sciences, LSU try and Neurology at the Tulane School During the weekend a "Town Hall" School of Medicine in New Orleans. He of Medicine, has received the Frieda meeting will be held in which members comes to Louisiana from Minneapolis Fromm-Reichmann Award of the Ameri- are invited to express their ideas, corn- where he served as Professor and Direc- can Academy of Psychoanalysis. -
Imitation: Is Cognitive Neuroscience Solving the Correspondence Problem?
ARTICLE IN PRESS TICS 384 Review TRENDS in Cognitive Sciences Vol.xx No.xx Monthxxxx Imitation: is cognitive neuroscience solving the correspondence problem? Marcel Brass1 and Cecilia Heyes2 1Department of Cognitive Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103 Leipzig, Germany 2Department of Psychology, University College London, Gower Street, London WC1E 6BT, UK Imitation poses a unique problem: how does the imi- framework (generalist theories) or whether it depends on tator know what pattern of motor activation will make a special purpose mechanism (specialist theories). We their action look like that of the model? Specialist then review research on the role of learning in imitation theories suggest that this correspondence problem has and observation of biological motion. Finally, we discuss a unique solution; there are functional and neurological a problem for generalist theories: If imitation depends on mechanisms dedicated to controlling imitation. General- ist theories propose that the problem is solved by general mechanisms of associative learning and action control. Box 1. Mirror neurons: What do they do? What are they for? Recent research in cognitive neuroscience, stimulated Mirror neurons in the premotor area F5 of monkeys are active both by the discovery of mirror neurons, supports generalist when the animal observes and when it executes a specific action solutions. Imitation is based on the automatic activation (for a review see [52,53]. The discovery of these cells has had a revolutionary impact, turning perception–action interaction into a of motor representations by movement observation. focus of intensive, interdisciplinary research worldwide. Naturally These externally triggered motor representations are there has been a great deal of speculation about the function of then used to reproduce the observed behaviour. -
How to Use Outlines to Teach Rhetorical Prosody and Structure
VANCE SCHAEFER AND LINDA ABE United States The Art of Imitation: How to Use Outlines to Teach Rhetorical Prosody and Structure onnative speakers of a language are often at a disadvantage in producing extended speech, as they have differing native (L1) N phonological systems and rhetorical traditions or little experience in giving talks. Prosody in the form of stress, rhythm, and intonation is a difficult but crucial area needed to master extended speech because prosody interacts with structure to play a key role in conveying meaning (i.e., intelligibility) and easing understanding (i.e., comprehensibility) (see Munro and Derwing 1995 for discussion on intelligibility, comprehensibility, and pronunciation). However, second-language (L2) speakers of rhetorical prosody and structure: namely, English might not effectively produce this putting the focus on using outlines. This rhetorical prosody. For example, they may article serves as a primer for practitioners not fully utilize pitch range to signal a shift of English as a second or foreign language in topics (Wennerstrom 1998), potentially (ESL/EFL), describing how to use outlines resulting in lower comprehension levels (Munro as an effective technique to teach rhetorical and Derwing 1995; Wennerstrom 1998). prosody and structure to learners at the level This difficulty appears to arise from a lack of high school, university, and beyond. This of understanding and/or effective practice, article covers the following: as gauged from our teaching experience. While the mechanics of academic writing and 1. a simple overview of prosody and grammar are taught to L2 English learners, the structure in English, described with rhetorical elements of prosody do not appear to concrete features and rules be commonly taught.