Plan Recognition

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Plan Recognition

  1. 1. A Smart Home Agent for Plan Recognition of Cognitively-impaired Patients 老師:張耀仁 學生:徐欣佑
  2. 2. Introduction <ul><li>Increasing problems in health field </li></ul><ul><ul><li>Population ageing </li></ul></ul><ul><ul><li>Medical staff shortages </li></ul></ul><ul><li>Smart home </li></ul><ul><li>Cognitive assistance </li></ul><ul><li>Plan recognition </li></ul>
  3. 3. Cognitive assistance <ul><li>Cognitive deficiencies such as </li></ul><ul><ul><li>Alzheimer’s disease </li></ul></ul><ul><ul><li>Schizophrenia </li></ul></ul><ul><li>Activities of Daily Living (ADL) </li></ul>
  4. 4. Plan recognition <ul><li>Identify the on-going inhabitant ADL from observed actions and events </li></ul><ul><li>Infer the goal pursued by the actor </li></ul><ul><li>Predict the behaviour of the observed agent </li></ul><ul><ul><li>Smart home (agent) </li></ul></ul><ul><ul><li>Occupant (patient) </li></ul></ul>
  5. 5. Plan recognition (continued) <ul><li>Intended plan recognition </li></ul><ul><ul><li>The patient knows that he is being observed and is adapting his behavior in order to make his intentions clear to the observer. </li></ul></ul><ul><li>Keyhole plan recognition </li></ul><ul><ul><li>The patient does not know that he is being observed or that he is not taking it into account </li></ul></ul>
  6. 6. Explore solutions <ul><li>Probabilistic methods </li></ul><ul><ul><li>Based on the Markovian model, Bayesian networks and Dempster-Shafer theory </li></ul></ul><ul><li>The learning techniques </li></ul><ul><ul><li>Build a probabilistic predictive model </li></ul></ul><ul><li>Logical approaches </li></ul><ul><ul><li>Find series of logical deductions </li></ul></ul>
  7. 7. The logical model of plan recognition <ul><li>Lattice theory </li></ul><ul><li>Action description logic </li></ul><ul><li>Classified through a lattice structure </li></ul><ul><li>Recognition space </li></ul>
  8. 8. Recognition space model <ul><li>Interpret the set of the observed actions </li></ul><ul><li>Predict the patient’s future actions </li></ul><ul><li>(GetGun , GotoBank ) equal? (Hunt or RobBank) </li></ul><ul><li>Recognition model </li></ul>
  9. 9. Action model overview <ul><li>Follows the lines of Description Logic (DL) </li></ul>:next state :current state is the precondition of expresses the effect of
  10. 10. Variable plan <ul><li>RobBank(GotoBank & GetGun) and Hunt(GotoWood & GetGun) </li></ul><ul><li>GotoBank and GotoWood are incomparable </li></ul><ul><li>A variable plan (x , GetGun) is the lower bound of this tow plans </li></ul><ul><li>The substitution domain of the variable x would be : </li></ul>
  11. 11. Plans composition <ul><li>Stability </li></ul><ul><ul><li>There is no possibily of introducing other external actions </li></ul></ul><ul><li>Closure </li></ul><ul><ul><li>Each plan must admit an upper bound and a lower bound </li></ul></ul>
  12. 12. Plans composition (continued) <ul><li>Observed action GetGun </li></ul><ul><li>The set of possible plans is </li></ul><ul><ul><li>{RobBank(GotoBank & GetGun), Hunt(GotoWood & GetGun)} </li></ul></ul><ul><li>The composition of the plans </li></ul><ul><ul><li>{(GotoBank,GotoWood,Getgun) ,(GotoWood,GotoBank,GetGun)} </li></ul></ul>
  13. 13. Recognition of activities in smart home <ul><li>Basic events are generated by sensors and are directly sent to agents </li></ul><ul><li>Low-level activity recognition (LAR) </li></ul><ul><li>High-level recognition service (HLRS) </li></ul>
  14. 14. Achitecture of the plan recognition system
  15. 15. Application of activities recognition
  16. 16. Low-level activity recognition
  17. 17. High-level recognition service
  18. 18. High-level recognition service (continued) <ul><li>Plans knowledge base </li></ul><ul><ul><li>WashDish(StartWasing , GotoKitchen) </li></ul></ul><ul><ul><li>PrepareTea(GetWater , GotoKitchen) </li></ul></ul><ul><ul><li>WatchTv(TurnOnTv , GotoLivingRoom) </li></ul></ul><ul><ul><li>Drink(GetWater) </li></ul></ul>
  19. 19. Recognition space lattice
  20. 20. Future experimentation <ul><li>Senile Dementia of the Alzheimer’s type </li></ul><ul><li>Kitchen Task Assessment (KTA) </li></ul><ul><ul><li>Places the objects at the right place </li></ul></ul><ul><ul><li>Complete description of the whole steps </li></ul></ul><ul><ul><li>Follow the indications </li></ul></ul><ul><ul><li>Note the patient’s errors </li></ul></ul>
  21. 21. Conclusion <ul><li>Lattice theory and action description logic </li></ul><ul><li>Minimizing uncertainty about the prediction of the observed behaviour </li></ul><ul><li>Inhabitant’s specific profile </li></ul><ul><li>Learned patient’s habits </li></ul>

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