#the first set of testing problems for the IPC 2014 competitors
# this is intended to be an easier problemset that:
#   (1) thins out the final list of competitors I need to 
#       run to determine a winner of each category     
#   (2) provides the baseline for who will be considered
#       for the best learner prize

#method for generation (prior to observing results from testing on training):
#  (1) take the testing subset from "testingFromTraining.txt"
#  (2) for each problem, randomly select new parameters within
#      the range of the problems in that set.  
#  (3) Generate random numbers with Python 2.7.3 (default, Feb 27 2014, 20:00:17) 
#      random.randint() function, which generates a number, N, in the
#      range R1, R2: R1 <= N <= R2. At the start of each problem, I set
#      the seed to "2014" for the first problem and seed to 2014N, 
#      where N is 2 thru 6 for other problems.  I then draw each number
#      from randint( R1, R2 ), observing the random sequence.

# elevators - p[floors]_[passengers].pddl
# p24_45_1.pddl
# p32_45_1.pddl
# p40_45_1.pddl
# p48_45_1.pddl
#create 5 problems
#seed 2014
#randomly select 24,32, or 40 floors;            randint(1,3): 1,  2,   3,  3,  2
#randomly select between 40 and 60 passengers; randint(40,60): 54, 40, 48, 42, 54
p24_54_1.pddl
p32_40_1.pddl
p40_48_1.pddl
p40_42_1.pddl
p32_54_1.pddl

#floortile p[rows]-[cols]-[robots].pddl
# p4-4-2.pddl
# p5-4-2.pddl
# p4-4-3.pddl
# p5-5-3.pddl
#create 5 problems
#seed 20142
#randomly select rows between 4-6;         randint(4,6): 4 5 4 6 4
#randomly select cols between between 3-6; randint(3,6): 3 4 3 4 5
#randomly select robots from 2 or 3;       randint(2,3): 2 2 2 3 3
#correct second instance of 4 3 2 to 4 3 3; cannot generate probs with same name 
p4-3-2.pddl
p5-4-2.pddl
p4-3-3.pddl
p6-4-3.pddl
p4-5-3.pddl

#nomystery p-[ratio]-[packages&locations].pddl
# p-c15-08.pddl
# p-c13-08.pddl
# p-c11-08.pddl
# p-c10-08.pddl
#create 5 problems
#seed 20143
#randomly select packages between 8-16;     randint(8,16):  9, 10, 12, 11, 15
#randomly select locations between (-2,2);  randint(-2,2): -2, -2, -2,  0, -1
#randomly select c from {1.5, 1.3, 1.1};    randint( 1,3):  3,  1,  1,  1,  1
p-c11-09-07.pddl
p-c15-10-08.pddl
p-c15-12-10.pddl
p-c15-11-11.pddl
p-c15-15-14.pddl

#parking p[curbs]-[cars].pddl
# p28-15.pddl
# p38-20.pddl
# p48-25.pddl
# p58-30.pddl
#create 5 problems
#seed 20144
#randomly select cars between 15-30; randint(15,30): 23, 24, 28, 23, 19, 19, 30
p44-23.pddl
p46-24.pddl
p34-28.pddl
p36-19.pddl
p58-30.pddl

#spanner prob-[spanners]-[nuts]-[locatins].pddl
# prob-130-130-80-1396209574.pddl
# prob-140-140-90-1396209574.pddl
# prob-150-150-100-1396209574.pddl
# prob-160-160-110-1396209574.pddl
#create 5 problems
#seed 20145
#randomly select num_spanners 130-160     randint(130,160): 143, 159, 150, 132, 130
#randomly select delta for num_nuts -4,4     randint(-4,4):   2,  -4,   0,   3,   3
#randomly select delta for num_locs 46-54   randint(46,54):  50,  53,  47,  47,  49
prob-143-145-93-1403129508.pddl
prob-159-155-106-1403129508.pddl
prob-150-150-103-1403129508.pddl
prob-132-135-85-1403129508.pddl
prob-130-3-49-1403129508.pddl

#transport p-[cities]-[locations]-[packages].pddl
# p-2-50-30.pddl
# p-2-60-25.pddl
# p-3-50-25.pddl
# p-3-60-20.pddl
#generate 5 problems
#seed 20146
#randomly select cities 2 or 3      randint(2,3):  3,  2,  3,  3,  3
#randomly select locations 50-60  randint(50,60): 58, 55, 55, 56, 60
#randomly select packages 20-35   randint(20,35): 27, 23, 31, 35, 27
p-3-58-27.pddl
p-2-55-23.pddl
p-3-55-31.pddl
p-3-56-35.pddl
p-3-60-27.pddl