Cooperative multi-agent planning (MAP) is a relatively recent research field that combines
technologies, algorithms, and techniques developed by the Artificial Intelligence Planning …

Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans,
that is, solutions to planning problems, that transform a given state of the world to another …

This paper presents two prototypical epistemic forward planners, called EFP and PG-EFP,
for generating plans in multi-agent environments. These planners differ from recently …

In many cases several entities, such as commercial companies, need to work together
towards the achievement of joint goals, while hiding certain private information. To …

It is essential for a collaborative robot to consider the Theory of Mind (ToM) when interacting
with humans. Indeed, performing an action in the absence of another agent may create false …

Abstract Multi-Agent Plan Recognition (MAPR) is the problem of inferring the goals and
plans of multiple agents given a set of observations. While previous MAPR approaches have …

Earlier epistemic planning systems for multi-agent domains generate plans that contain
various types of actions such as ontic, sensing, or announcement actions. However, none of …

It is essential for a collaborative robot to consider Theory of Mind (ToM) when interacting
with humans. Indeed, performing an action in the absence of another agent may create false …

We consider the human-aware task planning problem where a human-robot team is given a
shared task with a known objective to achieve. Recent approaches tackle it by modeling it as …

Interacting actions–actions whose joint effect differs from the union of their individual effects–
are challenging both to represent and to plan with due to their combinatorial nature. So far …