class_docstr: Q-learning agent with tabular representation.
class_docstr_tok: ["Q-learning","agent","with","tabular","representation","."]
code: def _adjust_exploration_rate(self):
      self._epsilon = self._parameters.epsilon_minimum + max(
          0,
          (
              self._parameters.initial_epsilon
              - self._parameters.epsilon_minimum
          )
          * (
              1
              - float(self.step_count)
              / self._parameters.epsilon_decay_step_count
          ),
      )
  
file_path: CNTK/bindings/python/cntk/contrib/deeprl/agent/tabular_qlearning.py
imports: import copy
  import numpy
  from .agent import AgentBaseClass
  from .shared.qlearning_parameters import QLearningParameters
label_desc: Use image node_id 10 for calling the TabularQLearning obj's underlying member method code with example usage: obj._adjust_exploration_rate() without return types