Considerable progress has been made toward understanding the neural computations underlying the capacity of the human brain to learn from experience and in making decisions to maximize future rewards. Much less is known about how the brain is able to learn and make decisions in a social context. In this talk I will outline a computational model-based approach in which we combine computational modeling with fMRI experiments in order gain insight into how it is that the brain is capable of learning from and about other people, as well as to ascertain how it is the brain can make use of the knowledge acquired about or from others in order to make good decisions in a social context. Our findings point to the involvement of multiple mechanisms in social learning and decision-making. These include neural systems that facilitate learning through observing the rewards obtained by others (vicarious reinforcement-learning), neural systems involved in imitating others' actions, and neural systems involved in making inferences about the hidden preferences, thoughts and intentions of others. I will further identify some of the key outstanding questions that will need to be addressed in order to gain a comprehensive understanding of how these systems interact to guide behavior in social contexts.