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Research Here and There

This research focuses on fuzzy relational databases and preference logic, including financial time series forecasting, learning ASP/action languages, medical decision support systems, and modeling interaction scenarios.

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Research Here and There

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  1. Research Here and There Zhizheng Zhang(张志政) Southeast University(东南大学)

  2. Here

  3. There

  4. Research Mathematical Problem World Models Languages Algorithms Ontology Interpretations

  5. Outline • Did • Fuzzy relational database • Financial Time Series Forecasting • Preference Logic • Doing • Learning ASP/Action Languages • Medical decsion support system • Modeling interaction scenario. • To do • Formalizing medical guidelines using action language • Logic for interaction • Logic programs sequences

  6. Did • Fuzzy Relational Database • World: linguistic variable+fuzzy raletions • Language: fuzzy SQL • Model: fuzzy relations theory • Problem: Fuzzy Query

  7. Financial Time Series Forecasting • World: exchange rate change history, concerning factors (e.g. oil price.) • Language: neural network, Baysian network, fuzzy rules…. • Model: Time Series xt+1=f(xt, xt-1,…,yt,yt-1,…) • Problem: What are the parameters’ values in a given language for a given world of histories.

  8. My work on preference logic • Provide an axiomization system with four kinds of preferences introduced in [1]. J. van Benthem, S. van Otterloo, and O. Roy. Preference logic, conditionals, and solution concepts in games. In H. Lagerlund,S. Lindström, and R. Sliwinski, editors, Modality Matters, 61–76, 2006. [2]. Johan van Benthem. Games in dynamic-epistemic logic. Bulletin of Economic Research, 53:219–248, 2001.

  9. ,  are propositional logic formula • > : there exist at least one model m of  and at least one model m’ of  such that m is better than m’. • > : there exist at least one model m of  such that m is better than every model of . • > : there exist at least one model m of  such that every model of  is better than it. • > : for any model m of  and any model m’ of , m is better than m’ .

  10. Satisfaction of a preference logic formula

  11. Preference Revision • Example, In valentine's day, based on your and your girlfriend’s usual preferences, your new preferences are romantic movie is better than other types of movies, and more stars is better.

  12. Doing • Learning ASP/Action Languages • Why: • Motivation Problems: • How to make new questions automatically according to a student’s QA histories and textbook knowledge in educational assistant systems? • How to diagnose a student’s psychological status according to his behaviors records and middle school students psychological knowledge? • We hope our programming languages are our natural languages.

  13. Medical decision support system • World: dynamic domain • Model: transition diagram • Language: action language • Problem: Planning • Difficulties: complex ontology, conflict knowledge, preferences.

  14. Modeling interaction scenario • Static Games. The status of agents are static • Dynamic Games. The behaviors of agents can change their preferences, beliefs.

  15. To Do • Formalizing some diseases prevention and cure guidelines using action language • I don’t know what difficulties we will meet. Maybe they include: uncertain, complex ontology, quantitative constriants, commonsense……etc.. • My question: Is “Modular” method good enough to model the complex domain for action languages? My thinking now: Yes, it is successful in C++ and jave, but need to test it in the real applications by using it to model domains with character of inheritance hierarchy.

  16. Logic for interaction • Axiomatization • If preferences are the basis of social choice, how to model the decision procedures when preferences are dynamic. • Computation issue of some interaction scenarios • Formalizing interaction procedures using ASP/AL • Why we have ASP sequences? • Beliefs are changing. • Prioritized goals • We formalize the open/evolving domain step by step • Every agent has its own belief on world, but they have to work together.

  17. Question:What is the rational “answer set” of ASP sequences? My thinking: 1). Rational answer sets of the sequences should also be those literals that we are forced to believe. 2). If the union of those ASP is consistent. GOOD! 3). Restoring consistency is rational if we can remove inconsistency by its causes and making a minimal change.

  18. What are the causes of inconsistencies in an ASP seqeuences? Example, P<Q (1). Indirect Exceptions P: {p:-c, not –p. q:-p.} Q: {c. –q} CR-Prolog is great!

  19. (2) not-cycle P: {a:-b.} Q: {b:-not a.} (3)Unsatisfied Constraints P: {:-a, b. a.} Q: {b.}

  20. (4) others? P: {a.} Q: {-a.} (5) Any others? How to deal with them?

  21. THANK YOU

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