This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
When reasoning about actions and sensors in realistic domains, the ability to cope with uncertainty often plays an essential role. Among the approaches dealing with uncertainty, t...
In order to generate plans for agents with multiple actuators or agent teams, we must be able to represent and plan using concurrent actions with interacting effects. Historically...
Our project aims at the automatic generation of multilingual text for product maintenance and documentation from a structured knowledge representation formalized by means of plans...
This paper presents a language for coordinating several logic-based agents capable of abductive reasoning. The system is particularly suited for solving problems with incomplete k...
Anna Ciampolini, Evelina Lamma, Paola Mello, Paolo...