Autonomous robots often need to operate with and around humans, to provide added value to the collaborative team, to earn-and-prove trustworthiness, as well as to utilize the support from the human team-mates. The presence of humans brings additional challenges for robot decision-making, but also opportunities for improving the decision-making capabilities with human help. Two major computational paradigms for sequential decision-making are planning and learning.