import tensorflow as tf

class ValueEstimator_MountainCarContinuous():
    def __init__(self, learning_rate=0.1, par_idx=0,scope="value_estimator"):
        w_init = tf.random_normal_initializer(0.,.1);
        with tf.variable_scope(scope+"_"+str(par_idx)):
            # state and target
            self.state = tf.placeholder(tf.float32, [None,400], "state")
            self.target = tf.placeholder(tf.float32, [None,1], name="target")

            # layers
            self.value_estimate = tf.layers.dense(self.state, 1, kernel_initializer=w_init, name='v')  # estimated value for state
