void testQLearningDummy() {
randomSeed(RANDOM_SEED);
NeuralNetwork net(DUMMY_ENVIRONMENT_OBSERVATIONS_DIM + DUMMY_AGENT_ACTIONS_DIM, N_HIDDEN, 1, 0.1f);
ActionProperties props(DUMMY_AGENT_ACTIONS_DIM, DUMMY_AGENT_N_ACTIONS);
QLearningEGreedyPolicy egreedy(0.1f);
QFunction qFunc(&net, DUMMY_ENVIRONMENT_OBSERVATIONS_DIM, &props);
QLearningAgent agent(&qFunc, &egreedy,
DUMMY_ENVIRONMENT_OBSERVATIONS_DIM,
&props,
0.0f, 0.01f, false); // lambda = 0.0 => no history, gamma = 0.01 => opportunistic agent
DummyEnvironment env;
testQLearning(env, agent);
}
Chain *filter(Chain *it, Quantifier qFunc) {
Chain *pass = NULL;
Chain *fail = NULL;
Chain *selector = NULL;
while (it != NULL) {
selector = fail;
if (qFunc(it->value) == True) {
selector = pass;
}
selector = prepend(selector, it->value);
it = it->next;
}
return pass;
}
BinaryVote *vote(Chain *it, Quantifier qFunc) {
Chain *pass = NULL;
Chain *fail = NULL;
Chain *selector = NULL;
while (it != NULL) {
selector = fail;
if (qFunc(it->value) == True) {
selector = pass;
}
selector = prepend(selector, it->value);
it = it->next;
}
BinaryVote *bv = newBinaryVote();
bv->pass = pass;
bv->fail = fail;
return bv;
}
