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| struct Set | pset |
| | Population set.
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| struct Set | prev_pset |
| | Previously stored population set.
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| struct Set | mset |
| | Match set.
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| struct Set | aset |
| | Action set.
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| struct Set | kset |
| | Kill set.
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| struct Set | prev_aset |
| | Previous action set.
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| struct ArgsAct * | act |
| | Action parameters.
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| struct ArgsCond * | cond |
| | Condition parameters.
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| struct ArgsPred * | pred |
| | Prediction parameters.
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| struct ArgsEA * | ea |
| | EA parameters.
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| struct EnvVtbl const * | env_vptr |
| | Functions acting on environments.
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| void * | env |
| | Environment structure (for built-in problems)
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| double | error |
| | Average system error.
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| double | mset_size |
| | Average match set size.
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| double | aset_size |
| | Average action set size.
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| double | mfrac |
| | Generalisation measure.
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| double | prev_reward |
| | Reward from previous step in a multi-step trial.
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| double | prev_pred |
| | Payoff prediction made on the previous step.
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| double * | pa |
| | Prediction array (stores fitness weighted predictions)
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| double * | nr |
| | Prediction array (stores total fitness)
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| double * | prev_state |
| | Environment state on the previous step.
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| double * | cover |
| | Values to return for a prediction instead of covering.
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| int | time |
| | Current number of EA executions.
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| int | pa_size |
| | Prediction array size.
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| int | x_dim |
| | Number of problem input variables.
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| int | y_dim |
| | Number of problem output variables.
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| int | n_actions |
| | Number of class labels / actions.
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| bool | explore |
| | Whether the system is currently exploring or exploiting.
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| double(* | loss_ptr )(const struct XCSF *, const double *, const double *) |
| | Error function.
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| double | GAMMA |
| | Discount factor for multi-step reward.
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| double | P_EXPLORE |
| | Probability of exploring vs. exploiting.
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| double | ALPHA |
| | Linear coefficient used to calculate classifier accuracy.
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| double | BETA |
| | Learning rate for updating error, fitness, and set size.
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| double | DELTA |
| | Fraction of population to increase deletion vote.
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| double | E0 |
| | Target error under which classifier accuracy is set to 1.
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| double | INIT_ERROR |
| | Initial classifier error value.
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| double | INIT_FITNESS |
| | Initial classifier fitness value.
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| double | NU |
| | Exponent used in calculating classifier accuracy.
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| double | HUBER_DELTA |
| | Delta parameter for Huber loss calculation.
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| int | OMP_NUM_THREADS |
| | Number of threads for parallel processing.
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| int | MAX_TRIALS |
| | Number of problem instances to run in one experiment.
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| int | PERF_TRIALS |
| | Number of problem instances to avg performance output.
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| int | POP_SIZE |
| | Maximum number of micro-classifiers in the population.
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| int | LOSS_FUNC |
| | Which loss/error function to apply.
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| int | TELETRANSPORTATION |
| | Maximum steps for a multi-step problem.
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| int | THETA_DEL |
| | Min experience before fitness used during deletion.
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| int | M_PROBATION |
| | Trials since creation a cl must match at least 1 input.
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| int | THETA_SUB |
| | Minimum experience of a classifier to become a subsumer.
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| int | RANDOM_STATE |
| | Random number seed.
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| bool | POP_INIT |
| | Pop initially empty or filled with random conditions.
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| bool | SET_SUBSUMPTION |
| | Whether to perform match set subsumption.
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| bool | STATEFUL |
| | Whether classifiers should retain state across trials.
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| bool | COMPACTION |
| | if sys err < E0: largest of 2 roulette spins deleted
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| char * | population_file |
| | Name of a JSON file containing an initial pop.
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XCSF data structure.
Definition at line 85 of file xcsf.h.
1.9.8