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Robotics AI Illusions of intelligence Alan Turing Lab: Combine sound and light exercises. Homework: Identify & describe problems with the automatic solution similar to ‘human’ and problems with the automatic solution very different Artificial Intelligence • Definitions? – Machine (computer) simulating human reasoning – Machine (computer) demonstrating surprisingly human intelligence • Problem for field: as soon as some AI research proves practical, it isn’t considered AI! – American Association for Artificial Intelligence (AAAI) http://www.aaai.org/AITopics/html/welcome.html – AAAI/Nova interview with Cynthia Breazeal http://www.pbs.org/wgbh/nova/sciencenow/3318/03.html Different strategies • Work to solve problem, using any technique that works • Work to understand how humans reason enough to implement these ways using computers (cognitive science) and use implementations to test ideas Methods • Symbolic manipulation (as opposed to numerical calculations) • Enumerating / expanding trees of possibility: branch-and-bound search • Expert systems: states and testing conditions. • Neural nets (and other forms of machine learning) Expert systems • Collection of rules: If (A, B, C) then do D • Using the expert system consists of going through the rules and doing the actions • Early example: medical diagnosis. – Do checks – Actions may be do another test – Arrive at diagnosis Neural nets • Modeled after how brain may work • Define graph (nodes, directed edges) – Nodes conditions – Edge from A to B if A leads to B • Different techniques for building and refining net, including trying many cases and putting weight on edge if it leads to good result • http://www.popsci.com/science/article/201001/robots-display-predator-prey-co-evolutionevolve-better-homing-techniques Pattern recognition • Need to extract measurable features • These constitute the signature • Compare to archive • Example: facial recognition. Features such as ratio of spaces between eyes to eyes to chin. Need to use ratios for such things. Topics/problems • Theorem proving: technique to assume negative and see if you reach a contradiction by trying all combinations. • Natural language processing for interface – My abominable abdomen project vs moon rocks query • Natural language processing for translation: currently has some success/utility • Speech recognition – Depends on size of language, restrictions and/or training Histor • Attempt to make use of outtakes from interviews used for documentary of Jacques Lipchitz, sculptor: 1970! • Use keywords linking to segments to have Jacques answer questions – Illusion only of natural language – System continually massaged – Updated to work with latest technology • If [art, Histor] moves you, you must be satisfied. Quote from Jacques Lipchitz about art in general. Can apply to using Histor. • AI? Eliza • 1960s program (parady) by Joseph Weizenbaum to emulate a therapist (Rogerian) • Relatively simple manipulation of patient’s remarks with randomly inserted stock questions. – “My head hurts.” “Why do you think your head hurts”. – “I feel bad today.” “What do you think about your mother.” • Fairly successful! Alan Turing • Significant theoretical work on computation (Decision Problem) • Worked at Bletchley Park during WWII on decoding German codes (Enigma machine): done by altering a coding machine • Worked various places, including Princeton, with Van Neumann, others, on early computers • Proposed way to build a chess machine • Defined Turing test Decision problem • Theoretical problem, set by Hilbert (1900) Entscheidungsproblem: What does it mean for something to be computable? • Turing (1936) produced 2 formulations (Turing machines & recursive functions) and proved them equivalent (and later proved these equivalent to a formulation of Post). Also proved limitations http://www.turing.org.uk/turing/ many others Turing machine • Infinite strip of tape • Machine has finite number of states. A state holds the definition of what to do when reading a 0 or 1 on the tape • Machine reading a spot on the tape can – Move (on tape) left or right or stop – Write something on tape (re-write) – Change state • Turing machine computes a function on an input if it stops. The result is the number on the tape (technically, answer is number of 1s on the tape or one more) Universal Turing machine • Encode a Turing machine to be a single number • A Universal Turing machine takes as input the number representing a TM plus input and produces the result that the TM would produce from that input Recursive functions • Functions from vectors/tuples to vectors/tuples • Built up from basic functions – Constant functions F(x1, x2, ..xk) = n – Successor function F(x) = x+1 – Projection Fik(x1, x2, ..xk) = xi • Using – Composition – Primitive recursion – Inverse (aka μ operator) Turing test • Set up a judge to have a ‘conversation’ using text messages back and forth to a machine and to a human. • If the judge cannot tell the difference, then the machine has passed the [Turing] test. • What about Histor? What about Eliza? Should the test be harder? Robotics • Robotics has been considered part of AI in computer science but also in engineering • Are AI techniques such as pattern recognition, expert systems, neural networks, especially applicable to physical tasks? Preview / Commercial • Fall course Advanced Topics in Computer Science will include computability, AI and encryption (including recent news about vulnerability of current practices), etc. • Beautiful • Exercise in logical thinking Lab • Follow line and turn around when there is a sound. • Your own idea. Ideas: – From outside the blue oval, start when someone claps, move to the circle and follow line. – From outside (especially track in the back), go in one direction and keep track of each blue line passed. Use variable (suitcase). Display count. – [Needs singing/hum] Start at rest. When sound is greater than a certain level, go around oval. If and when sound stops (falls), • turn to inside of oval and stop • leave oval – Add bump sensor (perhaps in back or combined with light?) • Your own challenge to the class? Homework • Identify a problem/task for which the automated solution/approach is – Similar to the human way – Different from the human way • Postings • Preview: AI topics are options for research presentation as are 'real world' robotics, real robots versus robots in literature, health, miltiary,ethics, etc.