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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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Contents. Problem Domain Overall Learning Process Application of ATC
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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)
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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)
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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)
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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)
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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
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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))
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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)]
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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...
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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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