Integrating Human Recommendations in the Decision Process of Autonomous Agents

In order to help agents in a difficult situation, we integrate the human in the agent´s decision process. We develop a new model called Human Help Provider in a Markov Decision Process (HHP-MDP). We define HHP-MDP as a middle ground between an autonomous agent and a teleoperated agent called adjustable autonomy. The global approach of HHP-MDP is based on (1) a recommendation is translated into a partial policy, (2)then, this partial policy is translated into transition and reward functions associated to the agent Markov Decision Process. This new model is quickly integrated into the agent´s decision process.