  Interactions within human societies are usually regulated by social norms. If
robots are to be accepted into human society, it is essential that they are
aware of and capable of reasoning about social norms. In this paper, we focus
on how to represent social norms in societies with humans and robots, and how
artificial agents such as robots can reason about social norms in order to plan
appropriate behavior. We use the notion of institution as a way to formally
define and encapsulate norms, and we provide a formal framework for
institutions. Our framework borrows ideas from the field of multi-agent systems
to define abstract normative models, and ideas from the field of robotics to
define physical executions as state-space trajectories. By bridging the two in
a common model, our framework allows us to use the same abstract institution
across physical domains and agent types. We then make our framework
computational via a reduction to CSP and show experiments where this reduction
is used for norm verification, planning, and plan execution in a domain
including a mixture of humans and robots.
