Recognizing the actions, plans, and goals of a person in an unconstrained environment is a
key feature that future robotic systems will need in order to achieve a natural human …

Recognising the goal of an agent from a trace of observations is an important task with many
applications. The state-of-the-art approach to goal recognition (GR) relies on the application …

Collaborative tasks often begin with partial task knowledge and incomplete initial plans from
each partner. To complete these tasks, agents need to engage in situated communication …

There are many scenarios in which a mobile agent may not want its path to be predictable.
Examples include preserving privacy or confusing an adversary. However, this desire for …

Goal Recognition is the task of inferring an agent's intentions from a set of observations.
Existing recognition approaches have made considerable advances in domains such as …

Despite some similarities that have been pointed out in the literature, the parallelism
between automated planning and natural language processing has not been fully analysed …

While classical planning has been an active branch of AI, its applicability is limited to the
tasks precisely modeled by humans. Fully automated high-level agents should be instead …

The ability to observe the effects of actions performed by others and to infer their intent, most
likely goals, or course of action, is known as a plan or intention recognition cognitive …

In real-time strategy (RTS) games, the ability of recognizing other players' goals is important
for creating artifical intelligence (AI) players. However, most current goal recognition …

In this report, we introduce an artificial dataset generator for Photo-realistic Blocksworld
domain. Blocksworld is one of the oldest high-level task planning domain that is well defined …