Intelligent Machines Vs. Human Intelligence
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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 . -
Can Machines Think?
Sandringham School Faculty of Computer Science Can Machines Think? This is a question posed by famous English Computer Scientist Alan Turing in Intelligent machines and programmes are judged. 1950. His ‘Turing Test’ has become the benchmark by which Artificially Recently, the Turing Test hit the news when a programme that simulated a 13 year old Ukrainian boy (called Eugene Goostman) managed to convince a third of testers that they were talking to a real human. http://www.bbc.co.uk/news/technology-27762088 http://www.reading.ac.uk/news-and-events/releases/PR583836.aspx http://www.alicebot.org/chatbots3/Eugene.pdf Your summer assignment is as follows: 1. 2. DesigningInvestigate a who fully Alan functional Turing Chatbot was and that explain can process in detail human what the language ‘Turing is oneTest’ of is the and most how difficult it is important tasks in in Computer the world Science. of Artificial Why Intelligence is this, what are the challenges? How did the Eugene Goostman bot overcome these? 3. Time to write your own Chatbot. In any language you choose (e.g. Python, Scratch, Java etc.), write a simple Chatbot. Clearly you will have to limit the questions that your bot can ask and the responses that it will Chatbot called Eliza at : https://groklearning.com/csedweek/hoc-eliza/ 4. What‘understand’! are the positiveIf you are implications totally stuck, for see the getting development started ofwith Artificial a simple Intelligence? What are the dangers to society of truly intelligent machines? Your assignment should be at least 4 pages of A4, excluding the programme listing. -
Language Technologies Past Present, and Future
Language technologies past present, and future Christopher Potts CSLI Summer Internship Program July 21, 2017 Many slides joint work with Bill MacCartney: http://web.stanford.edu/class/cs224u/ Hype and hand-wringing • Jürgen Schmidhuber: “We are on the verge not of another industrial revolution, but a new form of life, more like the big bang.” [link] • Elon Musk: “AI is a fundamental existential risk for human civilization, and I don't think people fully appreciate that.” [link] • October 2016: “Microsoft has made a major breakthrough in speech recognition, creating a technology that recognizes the words in a conversation as well as a person does.” [link] Two perspectives Overview • What is understanding? • A brief history of language technologies • Language technologies of the past • Language technologies of today • Current approaches and prospects • Predictions about the future! Readings and other background • Percy Liang: Talking to computers in natural language • Levesque: On our best behaviour • Mitchell: Reading the Web: A breakthrough goal for AI • Podcast: The challenge and promise of artificial intelligence • Podcast: Hal Daume on Talking Machines • Stanford CS224u, Natural language understanding What is understanding? To understand a statement is to: • determine its truth (with justification) • calculate its entailments • take appropriate action in light of it • translate it into another language • … The Turing Test (Turing 1950) Turing replaced “Can machines think?”, which he regarded as “too meaningless to deserve discussion” (p. 442), with the question whether an interrogator could be tricked into thinking that a machine was a human using only conversation (no visuals, no demands for physical performance, etc.). Some of the objections Turing anticipates • “Thinking is a function of man’s immortal soul. -
Theories of Intelligence, Learning, and Motivation As a Basis for Praxis
Theories of Intelligence, Learning, and Motivation as a Basis for Praxis Dr Eulalee Nderu-Boddington Ph.D. Education Assistant Professor at Prince Sultan University Riyadh Saudi Arabia May 26th 2008 ABSTRACT This paper examines how Piaget, Werner, and Gardner differ regarding the roles of cognition, intelligence, and learning in the developmental process. Piaget believes in the predominance of genetic factors. Werner stresses the influence of biological factors, while Gardner proposes that the environment plays a greater influence in how intelligence and learning are acquired. This paper also surveys research on achievement and learning strategies and their role in student motivation. The development of conceptual understanding is related to prior knowledge, interest, learning goals, and achievement goals. Introduction This paper focuses on the developmental theories of Werner, Gardner, and Piaget, all of whom have significantly influenced the field of education through their differing understandings of how students learn from childhood to adulthood. Most researchers agree that a combination of biology and environment affects personality and intelligence, but they differ in assigning relative importance to these two influences. Although poor nutrition, poor health care, and head injuries have been linked to poor IQ scores, for the most part environmental variables have not been found to account for a substantial portion of observed variations in human intelligence. Therefore, some psychologists believe heredity is the dominant influence on intelligence. They base their views on research that concentrates on variations among people in general cognitive ability or IQ. Others believe that such research overemphasizes the concept of IQ and gives too much credit to genetics (Azar, 1995). -
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. -
Passing the Turing Test Does Not Mean the End of Humanity
Cogn Comput (2016) 8:409–419 DOI 10.1007/s12559-015-9372-6 Passing the Turing Test Does Not Mean the End of Humanity 1 1 Kevin Warwick • Huma Shah Received: 18 September 2015 / Accepted: 20 November 2015 / Published online: 28 December 2015 Ó The Author(s) 2015. This article is published with open access at Springerlink.com Abstract In this paper we look at the phenomenon that is we do wish to dispel, however, is the assumption which the Turing test. We consider how Turing originally intro- links passing the Turing test with the achievement for duced his imitation game and discuss what this means in a machines of human-like or human-level intelligence. practical scenario. Due to its popular appeal we also look Unfortunately the assumed chain of events which means into different representations of the test as indicated by that passing the Turing test sounds the death knell for numerous reviewers. The main emphasis here, however, is humanity appears to have become engrained in the thinking to consider what it actually means for a machine to pass the in certain quarters. One interesting corollary of this is that Turing test and what importance this has, if any. In par- when it was announced in 2014 that the Turing test had ticular does it mean that, as Turing put it, a machine can been finally passed [39] there was an understandable ‘‘think’’. Specifically we consider claims that passing the response from those same quarters that it was not possible Turing test means that machines will have achieved for such an event to have occurred, presumably because we human-like intelligence and as a consequence the singu- were still here in sterling health to both make and debate larity will be upon us in the blink of an eye. -
Human Intelligence Differences: a Recent History Ian J
Forum TRENDS in Cognitive Sciences Vol.5 No.3 March 2001 127 Historical Perspective Human intelligence differences: a recent history Ian J. Deary Differences among humans in their mental important5. As a result of The Bell Curve’s that it does not emerge (Guilford, abilities are prominent, important, and controversies, the APA put together a task Thurstone, Gardner, Cattell and Horn); that controversial. In part, the controversy force of 11 people to write a report on there is a hierarchy of mental abilities from arises from over-uses and abuses of mental ‘Intelligence: Knowns and Unknowns’. The the general factor through broad ability tests, from insalubrious events in the individuals concerned came from different factors to very specific, narrow abilities history of mental test research, and from research traditions within and outside (Burt, Vernon) or that there is merely a lack of knowledge about what is and is not intelligence and were known to hold very range of uncorrelated narrow abilities currently known concerning human different views on the topic. Yet, they (Guilford)10,11. The resolution of these intelligence. In this article, some of the managed to produce a wide-ranging review debates was available from the 1940s, but well-attested facts about human intelligence article that all contributors signed. It not widely recognized. By 1939, Eysenck differences are summarized. A striking remains a touchstone for disinterested and showed that even Thurstone’s own data limitation of this body of research is that, authoritative information about intelligence contained a general factor that refuted his whereas much is known about the taxonomy differences. -
Intelligence Without Representation: a Historical Perspective
systems Commentary Intelligence without Representation: A Historical Perspective Anna Jordanous School of Computing, University of Kent, Chatham Maritime, Kent ME4 4AG, UK; [email protected] Received: 30 June 2020; Accepted: 10 September 2020; Published: 15 September 2020 Abstract: This paper reflects on a seminal work in the history of AI and representation: Rodney Brooks’ 1991 paper Intelligence without representation. Brooks advocated the removal of explicit representations and engineered environments from the domain of his robotic intelligence experimentation, in favour of an evolutionary-inspired approach using layers of reactive behaviour that operated independently of each other. Brooks criticised the current progress in AI research and believed that removing complex representation from AI would help address problematic areas in modelling the mind. His belief was that we should develop artificial intelligence by being guided by the evolutionary development of our own intelligence and that his approach mirrored how our own intelligence functions. Thus, the field of behaviour-based robotics emerged. This paper offers a historical analysis of Brooks’ behaviour-based robotics approach and its impact on artificial intelligence and cognitive theory at the time, as well as on modern-day approaches to AI. Keywords: behaviour-based robotics; representation; adaptive behaviour; evolutionary robotics 1. Introduction In 1991, Rodney Brooks published the paper Intelligence without representation, a seminal work on behaviour-based robotics [1]. This paper influenced many aspects of research into artificial intelligence and cognitive theory. In Intelligence without representation, Brooks described his behaviour-based robotics approach to artificial intelligence. He highlighted a number of points that he considers fundamental in modelling intelligence. -
The Turing Test
The Turing Test The Imitation Game: A computer (A) and a person (B) go head to head in a competition. The object is to convince a Judge (C) that they are both human. https://en.wikipedia.org/wiki/Turing_test In order to accomplish this, a computer needs to demonstrate intelligence. Turing believed that by the year 2000, this would be accomplished! https://classic.csunplugged.org/the-turing-test/ ELIZA, PARRY, Eugene Goostman https://www.zdnet.com/article/computer-chatbot-eugene-goostman-passes-the-turing-test/ https://www.codeproject.com/Articles/ 12454/Developing-AI-chatbots But what about Deep Blue & Watson…? Both programs were created by IBM. Deep Blue was able to defeat an international chess champion, while Watson defeated two Jeopardy champions at the same time. https://en.wikipedia.org/wiki/Watson_(computer) Bibliography Artificial Intelligence: The Turing Test. Accessed March 17, 2018. http://www.psych.utoronto.ca/users/reingold/courses/ai/turing.html. Bansa, Shubhan, “Turing Test in Artificial Intelligence." GeeksforGeeks. February 07, 2018. Accessed March 14, 2018. https://www.geeksforgeeks.org/turing-test-artificial- intelligence/. Bell, Steven. "Promise and Peril of AI for Academic Librarians | From the Bell Tower." Library Journal. April 14, 2016. Accessed March 15, 2018. https://lj.libraryjournal.com/2016/04/opinion/steven-bell/promise-and-peril-of-ai-for- academic-librarians-from-the-bell-tower/#_. "Computer AI Passes Turing Test in 'world First'." BBC News. June 09, 2014. Accessed March 17, 2018. http://www.bbc.com/news/technology-27762088. "Eliza, the Computer Therapist." Eliza, Computer Therapist. Accessed March 17, 2018. https://www.cyberpsych.org/eliza/. -
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. -
Passing the Turing Test Does Not Mean the End of Humanity
Passing the Turing Test Does Not Mean the End of Humanity Warwick, K & Shah, H Author post-print (accepted) deposited by Coventry University’s Repository Original citation & hyperlink: Warwick, K & Shah, H 2016, 'Passing the Turing Test Does Not Mean the End of Humanity' Cognitive Computation, vol 8, no. 3. DOI: 10.1007/s12559-015-9372-6 https://dx.doi.org/10.1007/s12559-015-9372-6 DOI 10.1007/s12559-015-9372-6 ISSN 1866-9956 ESSN 1866-9964 Publisher: Springer The final publication is available at Springer via http://dx.doi.org/10.1007/s12559- 015-9372-6 Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it. Passing the Turing Test Does Not Mean the End of Humanity Kevin Warwick and Huma Shah Coventry University, Priory Street, Coventry, CV1 5FB, UK Email: [email protected] , [email protected] Corresponding author: Kevin Warwick, tele: 44-247765-9893 Abstract: In this paper we look at the phenomenon that is the Turing test. -
AI Today, Beyond the Myth
AI today, beyond the myth Presented by:Ray Walshe For: ETSI Summit on Artificial Intelligence 04.04.2019 A Short History of Artificial Intelligence © ETSI 2019 Early Days • 1950 Alan Turing published “Computing Machinery and Intelligence” • “Imitation Game” see also John Searle’s “Chinese Room” • 1956 John McCarty held the first academic conference on the subject • The term artificial intelligence was coined • Marvin Minsky "Within a generation [...] the problem of creating 'artificial intelligence' will substantially be solved," © ETSI 2019 3 AI Winter • 1974–80 Initial optimism fades as progress in AI is slow • government funding stops • interest in the field drops off • Winter has begun • Thaw begins in 1980 • British government funds AI research again • Winter returns from 1987 to 1993 • Market Crash © ETSI 2019 4 AI Breakthrough • 1997 IBM's Deep Blue • Computer beats chess grandmaster Garry Kasparov. • 2011 IBM Watson • Watson's question‐answering system won the American quiz show "Jeopardy!" • beats reigning champions Brad Rutter and Ken Jennings • 2014 Chatbot called Eugene Goostman passes Turing test? © ETSI 2019 5 AI today • Art • Data Centres • Music • Sentiment Analysis • Fraud • Customer behaviour • Healthcare • Cyberbullying • Autonomous Vehicles • News and Media • Recommendations • Fishing © ETSI 2019 6 AI Computing © ETSI 2019 AI Hardware Three types of AI computing • Centralized environment, all calculations are done on one particular computer system, such as a dedicated server for processing data. • the single server model bottleneck • Distributed computing, not all transactions are processed in the same location, but that the distributed processors are still under the control of a single entity. • SETI • Decentralized computing, on its end, entails that no one single entity has control over the processing.