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.