n_obsn_actions env observation_space nenv action_space obs_t_ph tf placeholder(shape=[ n_obs]dtype=tf float obs_tp _ph tf placeholder(shape=[ n_obs]dtype=tf float act_ph tf placeholder(tf int shape=()rew_ph tf placeholder(shape=()dtype=tf float q_target_ph tf placeholder(shape=[ n_actions]dtype=tf float setup computation graph tf variable(tf random_uniform([n_obsn_actions] )q_current tf matmul(obs_t_phwq_target tf matmul(obs_tp _phwq_target_max tf reduce_max(q_target_phaxis= q_target_sa rew_ph discount_factor q_target_max q_current_sa q_current[ act_pherror tf reduce_sum(tf square(q_target_sa q_current_sa)pred_act_ph tf argmax(q_current setup optimization trainer tf train gradientdescentoptimizer(learning_rate=learning_rateupdate_model trainer minimize(errorwith tf session(as sessionsession run(tf global_variables_initializer()for episode in range( num_episodes )