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Bridging Artificial Intelligence, Psychometrics, and Economics: New Theory of Intelligence & Rationality

Bridging Artificial Intelligence, Psychometrics, and Economics: New Theory of Intelligence & Rationality

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Bridging Artificial Intelligence, Psychometrics, and Economics: New Theory of Intelligence & Rationality

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  1. Bridging Artificial Intelligence, Psychometrics, and Economics: New Theory of Intelligence & Rationality Selmer Bringsjord and Bettina Schimanski “A Science Based Approach to Decision-Making” Co-sponsored by the Dept. of Economics and the Dept. of Cognitive Science Friday, November 21, 2003

  2. A New Kind of AI An Answer To: What is AI? • Not an easy question to answer. • Assume the ‘A’ part is easy: we know what an artifact is. (Webster: “Something created by humans usually for a practical purpose.”) • There is no agreement on what human intelligence is. • Two notorious conferences. See The g Factor. • But we can agree that one great success of psychology is testing, and prediction on the basis of it. (The Big Test)

  3. Psychometric Artificial Intelligence • AI is, or at least ought to be, PAI. (pronounced “Pi”, rhymes with ) • PAI offers a simple but radical answer: • (Naïve definition): AI is the field devoted to building intelligent artificial agents, i.e., agents capable of solid performance on intelligence tests. • Don’t confuse with: “Some human is intelligent…”

  4. Psychometric AI is not completely new • Early roots: PAI was implicitly entertained with Evan’s 1968 ANALOGY program • However, PAI cannot be based on tests which consist solely of geometric analogies

  5. Other roots • Alan Newell’s 1973 “You Can’t Play 20 Questions With Nature and Win” • Does mention briefly possible PAI origins before his conclusion • “.. An alternative mold for such a task is to construct a single program that would take a standard intelligence test, say the WAIS or the Stanford-Binet.”

  6. Improved Definition of PAI • Psychometric AI is the field devoted to building information-processing entities capable of at least solid performance on all established, validated tests of intelligence and mental ability, a class of tests that includes IQ tests, tests ofreasoning, of creativity, mechanical ability, and so on.

  7. Broad Test: WAIS Wechsler Adult Intelligent Scale WAIS includes many sub-tests • The Comprehension sub-test is so difficult it could be a motivator for the original CYC dream • Deals with ordinary conversation Block Design - PERI has already cracked this Picture Arrangement - Deals with many mental facets PERI should specifically solve all of the WAIS - From there, we move to all other established tests Ex: “Why are the tires of automobiles made of rubber, rather than, say, plastic?”

  8. PAI (continued) • A full defense of PAI is beyond the scope of this short presentation, but that defense includes analysis of competing answers. • One such main competing answer is due to Stuart Russell’s work on formal accounts of rationality from the perspectives of AI and economics.

  9. Rationality and Intelligence • “Productive research in AI, both practical and theoretical, benefits from a notion of intelligence that is precise enough to allow the cumulative development of robust systems and general results. The concept of rational agency has long been considered a leading candidate to fulfill this role”.

  10. The agent receives percepts from the different environments and generates a behavior or result that in turn causes the environment to generate a state history. The performance measure evaluates the state history to arrive at the value of the agent. Figure from Stuart Russell’s Rationality and Intelligence ’02.

  11. Rationality • Perfect Rationality • Calculative Rationality • Bounded Rationality • Asymptotic Bounded Rationality

  12. Perfect Rationality The capacity to generate maximally successful behavior given the available information. Fundamental inputs include: E = the environment class in which the agent is to operate U = the performance measure V(f,E,U) = the expected value according to U obtained by an agent function f in environment class E. Then a perfectly rational agent is defined by an agent function fopt such that: This is just a fancy way of saying that the best agent does the best it can.

  13. Calculative Rationality The in-principle capacity to compute the perfectly rational decision given the initially available information. Calculative rationality is displayed by programs that, if executed infinitely fast, would result in perfectly rational behavior. Unlike perfect rationality, calculative rationality is a requirement that can be fulfilled by many real programs. On the other hand, calculative rationality is not necessarily a desirable property.

  14. Bounded Optimality (BO) The capacity to generate maximally successful behavior given the available information and computational resources. Fundamental Inputs include: Agent(p,M) = the agent function implemented by the program p running on machine M PM = finite set of all programs that can be run on M Therefore the bounded optimal program popt is defined by: Simply put, this is the notion of finding the program that generates the optimal feasible solution given the environment class E and performance measure U.

  15. Objection • Bounded Optimality limits R&D to the here and now. • We want to be able to analyze and achieve successful results irrespective of the limitations of computers today. Compare describing the running time of algorithms in terms of the O( ) notation (i.e. Big O). This provides a way to describe the complexity independent of machine speeds and implementation details. For this reason we investigate Asymptotic Bounded Rationality.

  16. Asymptotic Bounded Optimality (ABO) where kM denotes a version of M speeded up by a factor of k (or with k times more memory) and V*(f, E, U, n) is the minimum value of V(f, E, U) for all e E of complexity n. This means that the program is basically along the right lines if it just needs a better (i.e. faster or larger) machine to have worst-case behavior as good as that of any other program in all environments.

  17. More Objections • Russell’s approach is based on his view that intelligence consists of making changes to an environment external to the agent. • Problem: A mind able to think about things intelligently, independent of making changes in an external environment, might not only be intelligent but perhaps in fact ingenious?

  18. Our Theory Environment classes correspond to those for each sub-test. The performance measure is the grading of the results of the test. The utility is the score. Top loop of diagram corresponds to agent taking the test.

  19. Our approach in terms of Bounded Optimality • For PAI, one might say you cannot tackle a particular test with, say, a 22-state machine. • But such a restriction might well preclude getting at the “essence” of a test – or at the essence of what a test is a portal to. • Our view of intelligence / rationality is therefore, in general, calculative.

  20. Psychometric Experimental Robotic Intelligence (PERI) • Scorbot-ER IX • Sony B&W XC55 Video Camera • Cognex MVS-8100M Frame Grabber • Dragon Naturally Speaking Software • NL (Carmel & RealPro?) • BH8-260 BarrettHand Dexterous 3-Finger Grasper System

  21. Future work with PERI • Thwarting Terrorism • Picture Arrangement sub-test of WAIS • Natural Language Processing and Generation • Vision (Interpretation)

  22. Narratological Reasoning & Thwarting Terrorism… • Terrorists struggle to make stories real. • Their behavior can be anticipated, and thus • thwarted. • We need computers that can imagine future • events in a (twisted) narrative. • Threat anticipation (Picture Arrangement) • Predictive power done quickly ….

  23. RAIR Web and R&D Advanced Synthetic Characters MARMML PERI Savant PAI Slate CDs Super Teaching

  24. Questions? • For more detailed inquiries, visit our webpage: •