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Exploring the Constraints of Human Behavior Representation

Exploring the Constraints of Human Behavior Representation . A Masters Project Presentation John C. Giordano Prof. Paul Reynolds - Advisor. Outline. Introduction & problem statement Key terms Highlights of literature review Findings

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Exploring the Constraints of Human Behavior Representation

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  1. Exploring the Constraints of Human Behavior Representation A Masters Project Presentation John C. Giordano Prof. Paul Reynolds - Advisor John C. Giordano – Masters Project Presentation

  2. Outline • Introduction & problem statement • Key terms • Highlights of literature review • Findings • Proposed framework for considering human behavior representation (HBR) capabilities • Conclusions John C. Giordano – Masters Project Presentation

  3. “We can only see a short distance ahead, but we can see plenty there that needs to be done.” Alan Turing Computing Machinery and Intelligence In Mind: 236, 1950 John C. Giordano – Masters Project Presentation

  4. Introduction • In 1950, Alan Turing proposes the Imitation Game • Machines competing with or replacing humans • Human behavior representation (HBR) refers to the portrayal of humans • HBR is not Artificial Intelligence • More constrained • Still a challenge John C. Giordano – Masters Project Presentation

  5. What is the Problem? • HBR is critical to many, but has proven elusive • Several large-scale development failures with prominent HBR requirements • DoD’s Joint Simulation System (JSIMS) • NASA’s Air Traffic Management (ATM) simulation • Shortcomings noted by many in the community John C. Giordano – Masters Project Presentation

  6. How We Attempt to Address It • Examined successes and failures in research, design and implementation • Describe what is currently attainable and propose what is unachievable • Present a framework for assessing HBR capabilities • Seeking publication of research conducted to date John C. Giordano – Masters Project Presentation

  7. Key Terms • HBR: a computer-based model that mimics either the behavior of a single human or the collective action of a team of humans • Intelligent Software Agent: an artificial agent that operates in a software environment and imitates human intelligence by mechanical means in pursuit of the goals of its clients • Human Cognition:the process of receiving, processing, storing, and using information in humans John C. Giordano – Masters Project Presentation

  8. Literature Review • Over 60 publications (papers, journal articles, texts, tech reports, requirements documents) • Extended annotated bibliography • Thorough, but not fully exhaustive John C. Giordano – Masters Project Presentation

  9. Literature Review • Modeling Human and Organizational Behavior. Richard W. Pew and Anne S. Mavor (eds.). National Academy Press, Washington DC, 1998. • Techniques for Modeling Human Performance in Synthetic Environments: A Supplemental Review. Frank E. Ritter, et al. Human Systems Information Analysis Center, Wright Patterson AFB, OH, 2002. • A Taxonomy of Human Behavior Representation Requirements. Scott Y. Harmon. 11th Conference on Computer Generated Forces and Behavior Representation, 2002. John C. Giordano – Masters Project Presentation

  10. Harmon’s Taxonomy John C. Giordano – Masters Project Presentation

  11. Harmon’s Taxonomy John C. Giordano – Masters Project Presentation

  12. Harmon’s Taxonomy John C. Giordano – Masters Project Presentation

  13. Findings John C. Giordano – Masters Project Presentation

  14. Findings • The tools used to model and simulate HBR are constrained • The phenomena associated with HBR are highly complex • At times, HBR requirements vastly exceed capabilities • Capabilities and constraints should be clearly articulated to the community • Some capabilities may (only) be attained with the emergence of a disruptive technology John C. Giordano – Masters Project Presentation

  15. Some Tools • Soar: general cognitive architecture for intelligent agents • COGNET/iGEN: emulator for human decision-making and problem-solving • ACT-R: architecture for human cognition John C. Giordano – Masters Project Presentation

  16. Three Categories of HBR Capabilities John C. Giordano – Masters Project Presentation

  17. Mature Capabilities • Constrained speech recognition, parsing and generation • Course of Action (COA) analysis, selection and implementation • Rudimentary emotions • Human physiological characteristics • Semi-automated coarse-grained behavior generation • Probabilistic human performance simulation and prediction John C. Giordano – Masters Project Presentation

  18. Developing Capabilities • Autonomous, convincing group behavior • COA generation • Interdependence between physiology, emotion and cognition John C. Giordano – Masters Project Presentation

  19. Developing and Unachievable • Behavior adaptation appropriate to dynamic scenarios • Speech generation w/ appropriate prosody • Pattern recognition coupled w/ appropriate decision-making • Generalized behavior prediction • A single framework for modeling human behavior at multiple levels of resolution John C. Giordano – Masters Project Presentation

  20. Unachievable in Practice • Complex cognition, reasoning and learning • Conversational dialogue • Synthesis of autonomous knowledge acquisition, planning and behavior • Complete integration between emotion, cognition and behavior John C. Giordano – Masters Project Presentation

  21. A Generational Framework forConsidering HBR Capabilities • Analogous to the generations of programming languages • Generations • 1st: speech recognition, rudimentary emotions/physiology, probabilistic performance • 2nd: domain-independent speech, COA generation, adaptive behaviors • 3rd: single cognitive framework, architecture for multi-resolution behavior modeling, etc. • 4th: approaching human faculties John C. Giordano – Masters Project Presentation

  22. A Generational Framework forConsidering HBR Capabilities General Autonomous learning and planning Conversational dialogue Fourth Generation Model Specificity Third Generation Second Generation First Generation Concrete Speech recognition Integrated emotion and cognition Measurable Not Measurable Modeled Phenomenon John C. Giordano – Masters Project Presentation

  23. Conclusions • Turing foresaw human-machine competition – HBR comprises portrayal • Requirements development needs improvement • Opportunities for continued research John C. Giordano – Masters Project Presentation

  24. Future Work • Update and extend Pew and Mavor, Ritter et al. • Focus on HBR successes, particularly with promise of generalization • Rigorous, formalized HBR requirements John C. Giordano – Masters Project Presentation

  25. Questions? “It takes some philosophical discipline, in short, to resist specious blurrings of differences between simulations and the phenomena they simulate.” Larry Crockett In The Turing Test and the Frame Problem: AI’s Mistaken Understanding of Intelligence Intellect Books, 1994 John C. Giordano – Masters Project Presentation

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