There has been significant interest of late in generating behavior of agents that is
interpretable to the human (observer) in the loop. However, the work in this area has …

Whether a robot can perform some specific task depends on several aspects, including the
robot's sensors and the plans it possesses. We are interested in search algorithms that treat …

This paper introduces a novel approach to ontology-based robot plan transfer using
functorial data migrations from category theory. Functors provide structured maps between …

The increasing deployment of robots in co-working scenarios with humans has revealed
complex safety and efficiency challenges in the computation of the robot behavior …

We examine a novel setting in which two parties have partial knowledge of the elements that
make up a Markov Decision Process (MDP) and must cooperate to compute and execute an …

To treat sensing limitations (with uncertainty in both conflation of information and noise) we
model sensors as covers. This leads to a semilattice organization of abstract sensors that is …

For robots acting in the presence of observers, we examine the information that is divulged if
the observer is party to the robot's plan. Privacy constraints are specified as the stipulations …

We study a model in which a robot executes a plan whilst being observed. The observer is
interested in learning about the robot and its environment, and processes a sequence of …

The ability to reason about other agents' beliefs has many applications in multi-agent
systems, including facilitating coordinated behavior, teamwork, and information exchange …