AMPLE locates likely failure-causing classes by comparing method call sequences of passing and failing runs. A difference in method call sequences, such as multiple deallocation ...
Valentin Dallmeier, Christian Lindig, Andreas Zell...
This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed ...
Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee S...
Our approach to the spatial coordination problem relies on parametrized force fields. Through a quantitative comparison on a complex spatial coordination problem treated with a s...
This paper presents a new and innovative approach called mission-based just in time agent generation. The approach allows agents to be constructed on the fly, at run-time and just...
Glenn T. Jayaputera, Seng Wai Loke, Arkady B. Zasl...
We present a novel approach to multiagent planning for self-interested agents. The main idea behind our approach is that multiagent planning systems should be built upon (single-a...
Roman van der Krogt, Nico Roos, Mathijs de Weerdt,...