Incremental and Non-incremental Learning of Control Knowledge ...

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Discussion Related work 28 Linear: strips [Fikes et al., 1972], Rubik’s cube [Korf, 1985], prodigy/ebl [Minton, 1988], static [Etzioni, 1993], dynamic [Pérez and Etzioni, 1992], alpine [Knoblock, 1991], grasshoper [Leckie and Zukerman, 1998], lex [Mitchell et al., 1983], acm [Langley, 1983], lebl [Tadepalli, 1989], dolphin [Zelle and Mooney, 1993], experimenter [Carbonell and Gil, 1990], . . . Nonlinear “classical”: soar [Laird et al., 1986], failsafe [Bhatnagar, 1992], observe [Wang, 1994], composer [Gratch and DeJong, 1992], priar [Kambhampati, 1989], snlp+ebg [Kambhampati and Kedar, 1991], snlp+ebl [Katukam and Kambhampati, 1994], ucpop+ebl [Qu and Kambhampati, 1995], quality [Pérez and Carbonell, 1994], SteppingStone [Ruby and Kibler, 1992], ucpop+foil [Estlin and Mooney, 1995], pipp [Upal and Elio, 1998], prodigy/analogy [Veloso, 1994], DerSNLP [Ihrig and Kambhampati, 1996], hamlet [Borrajo and Veloso, 1997], evock [Aler et al., 2002], ExEL [Reddy and Tadepalli, 1999], . . .
Discussion More related work 29 Nonlinear “non classical”: rewrite rules [Ambite et al., 2000, Upal and Elio, 2000], camel [Ilghami et al., 2002], htn models [Garland et al., 2001], graphplan+ebl [Kambhampati, 2000], satplan+foil [Huang et al., 2000], generalized policies [Khardon, 1999, Martín and Geffner, 2000], hap [Vrakas et al., 2003] MDP models: reinforcement learning [Kaelbling et al., 1996], Q-learning [Watkins and Dayan, 1992], temporal differences [Sutton, 1988, Tesauro, 1992], lope [García-Martínez and Borrajo, 2000]
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Page 7 and 8: Motivation Our solution 4 Increment
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Page 37 and 38: Learning by genetic programming. ev
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Page 45 and 46: Discussion Incrementality 31 Increm
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Page 49 and 50: Discussion General discussion 33 Le
Page 51 and 52: Discussion Still to be solved. Zeno
Page 53 and 54: 37 Referencias [Aler et al., 2002]
Page 55 and 56: 39 [Ilghami et al., 2002] Okhtay Il
Page 57 and 58: 41 [Minton, 1988] Steven Minton. Le
Page 59: 43 Proceedings of the Second Intern

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