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Ch. 15 Acquiring First-order Knowledge About Air Traffic Control Yves Kodratoff and Christel Vrain 발표자 : 권 용 식.

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Presentation on theme: "Ch. 15 Acquiring First-order Knowledge About Air Traffic Control Yves Kodratoff and Christel Vrain 발표자 : 권 용 식."— Presentation transcript:

1 Ch. 15 Acquiring First-order Knowledge About Air Traffic Control Yves Kodratoff and Christel Vrain 발표자 : 권 용 식

2 Contents. Problem Domain Overall Learning Process Application of ATC

3 Air Traffic Control(ATC) avoid the crash of an aircraft –if collision is possible, modify the route of the planes AF2470(1) (2) BR1667(1) (2)

4 Representation of Knowledge and Generalization Trade-off –expressive power –computational complexity Generalization –By using background knowledge BK  x  y owns(x,y)  car(y)  driver(x,y)  x new_driver(x)  driving_license(x) driving_license(John)  owns(John, C1)  car(C1) new_driver(Bob)  owns(Bob,C2)  car(C2)  driving_license(X)  owns(X,C)  car(C)

5 Overall Learning Process determine the concepts to learn acquire background knowledge gather positive and negative examples generalize validate the knowledge Determination of the Concepts Rules: if G(x) then C(x) Positive and Negative Examples Background Knowledge Generalization Tool Validation Concept C(x)

6 Choose the Language Representation choosing the basic vocabulary choosing the formalism, propositional or predicate, attribute-value representation etc. –ex) (color_eyes, John, Brown) attribute(OBJECT,VALUE) –color_eyes(John, Brown) value(OBJECT, ATTRIBUTE) –brown(John, color_eyes) pred(OBJECT, ATTRIBUTE, VALUE) –physical_descr(John, color_eyes, Brown) attribute(OBJECT, C)  value(C) –color_eyes(John, C)  brown(C)

7 Determine the Concepts to Learn The aim of this application is to learn decision rules used by a human controller. Define some actions that can be performed on aircraft to avoid an impending accident –Do nothing: the action is performed on the other aircraft –Change of direction which is a temporary modification of the route –Change of route of the aircraft –... A solution of a conflict is a combination of these actions

8 Obtain the Examples and Rewriting Them Obtain the “Raw” Examples Rewrite (  (present_work_load PWL1)(steady PWL1) (destination AF2470 DESTINATION1)(west_european DESTINATION1) (destination AF2470 DESTINATION2)(far_away DESTINATION2) (solution AF2470 SOLUTION1)(change_direction SOLUTION1) (right SOLUTION1) (solution BR1667 SOLUTION2))

9 Rewrite BK as Horn Clauses IF a given plan has a steady trajectory when entering, exiting the sector and inside the sector, THEN it is on cruise  x  y  z  t[[traj_enter(x,y)  steady(y)  traj_in(x,z)  steady(z)  traj_exit(x,t)  steady(t)]  fl[flight(x,fl)  cruising(fl)]]  x  y  z  t[[traj_enter(x,y)  steady(y)  traj_in(x,z)  steady(z)  traj_exit(x,t)  steady(t)]  flight(x,f(x,y,z,t)]]  x  y  z  t  fl[[traj_enter(x,y)  steady(y)  traj_in(x,z)  steady(z)  traj_exit(x,t)  steady(t)  flight(x,fl)]  cruising(fl)]

10 Generalize and Rewrite G = (  (present_work_load vg3)(steady vg3)(destination vg1, vg21) (destination vg2 vg22)…(solution vg1 vg26)(change_direction vg26) (solution vg2 vg27) Foreseen work load - steady Estimation of the angle of the routes of the aircraft before conflict occurrence - sharp convergence Solution - vg1: change of direction...

11 Conclusion Transformation of the examples and the expert’s knowledge in first order, and transformation of learning back into a representation are not trivial. The success of the learning process often relies on a proper choice of the formalism Background knowledge is often incomplete, so validation of learning is important. There is still no full automation of ATC.


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