We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...
In this article we work on certain aspects of the belief change theory in order to make them suitable for argumentation systems. This approach is based on Defeasible Logic Program...
This paper formalizes a well-known psychological model of emotions in an agent specification language. This is done by introducing a logical language and its semantics that are u...
Bas R. Steunebrink, Mehdi Dastani, John-Jules Ch. ...
Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a local...
Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. K...