def process_experiences(self, current_info: AllBrainInfo, next_info: AllBrainInfo):
        """
        Checks agent histories for processing condition, and processes them as necessary.
        Processing involves calculating value and advantage targets for model updating step.
        :param current_info: Current AllBrainInfo
        :param next_info: Next AllBrainInfo
        """
        info_student = next_info[self.brain_name]
        for l in range(len(info_student.agents)):
            if info_student.local_done[l]:
                agent_id = info_student.agents[l]
                self.stats['Environment/Cumulative Reward'].append(
                    self.cumulative_rewards.get(agent_id, 0))
                self.stats['Environment/Episode Length'].append(
                    self.episode_steps.get(agent_id, 0))
                self.cumulative_rewards[agent_id] = 0
                self.episode_steps[agent_id] = 0
Checks agent histories for processing condition, and processes them as necessary.
        Processing involves calculating value and advantage targets for model updating step.
        :param current_info: Current AllBrainInfo
        :param next_info: Next AllBrainInfo