TEMPORAL DIFFERENCE LEARNING AND TD-GAMMON

[1] [Anonymous], 1990, ADV NEURAL INF PROCE

[2] COMPUTER BACKGAMMON [J]. SCIENTIFIC AMERICAN, 1980, 242 (06) : 64 - &

[3] Dayan P, 1994, ADV NEURAL INFORM PR, P817

[4] TOWARD AN IDEAL TRAINER [J]. MACHINE LEARNING, 1994, 15 (03) : 251 - 277

[5] FAWCETT TE, 1992, MACHINE LEARNING /, P144

[6] MULTILAYER FEEDFORWARD NETWORKS ARE UNIVERSAL APPROXIMATORS [J]. NEURAL NETWORKS, 1989, 2 (05) : 359 - 366

[7] ISABELLE JF, 1993, THESIS U MONTREAL

[8] MAGRIEL P, 1976, BACKGAMMON

[9] Robertie B., 1992, INSIDE BACKGAMMON, V2, P14

[10] Rumelhart DE, 1986, ENCY DATABASE SYST, P45

[1] [Anonymous], 1990, ADV NEURAL INF PROCE

[2] COMPUTER BACKGAMMON [J]. SCIENTIFIC AMERICAN, 1980, 242 (06) : 64 - &

[3] Dayan P, 1994, ADV NEURAL INFORM PR, P817

[4] TOWARD AN IDEAL TRAINER [J]. MACHINE LEARNING, 1994, 15 (03) : 251 - 277

[5] FAWCETT TE, 1992, MACHINE LEARNING /, P144

[6] MULTILAYER FEEDFORWARD NETWORKS ARE UNIVERSAL APPROXIMATORS [J]. NEURAL NETWORKS, 1989, 2 (05) : 359 - 366

[7] ISABELLE JF, 1993, THESIS U MONTREAL

[8] MAGRIEL P, 1976, BACKGAMMON

[9] Robertie B., 1992, INSIDE BACKGAMMON, V2, P14

[10] Rumelhart DE, 1986, ENCY DATABASE SYST, P45