<s> from pybrain . rl . agents . linearfa import LinearFA_Agent <EOL> from pybrain . rl . experiments import EpisodicExperiment <EOL> from environment import Environment <EOL> from tasks import LinearFATileCoding3456BalanceTaskCleverReward <EOL> from training import LinearFATraining <EOL> from learners import SARSALambda_LinFA_ReplacingTraces <EOL> task = LinearFATileCoding3456BalanceTaskCleverReward ( ) <EOL> learner = SARSALambda_LinFA_ReplacingTraces ( task . nactions , task . outdim ) <EOL> learner . _lambda = <NUM_LIT> <EOL> task . discount = learner . rewardDiscount <EOL> agent = LinearFA_Agent ( learner ) <EOL> agent . epsilonGreedy = True <EOL> agent . init_exploration = <NUM_LIT:0.5> <EOL> agent . logging = False <EOL> performance_agent = LinearFA_Agent ( learner ) <EOL> performance_agent . logging = False <EOL> performance_agent . greedy = True <EOL> performance_agent . learning = False <EOL> experiment = EpisodicExperiment ( task , agent ) <EOL> learner . learningRateDecay = <NUM_LIT> <EOL> tr = LinearFATraining ( '<STR_LIT>' , experiment , <EOL> performance_agent , verbose = True ) <EOL> tr . train ( <NUM_LIT> , performance_interval = <NUM_LIT:1> , n_performance_episodes = <NUM_LIT:1> , <EOL> serialization_interval = <NUM_LIT:50> ) </s>
