With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
Building upon the interactive inversion method introduced by Ashburn and Bonabeau (2004), we show how to dramatically improve the results by exploiting modularity and by letting t...
We extend a recent approach to integrate action formalisms and non-monotonic reasoning. The resulting framework allows an agent employing an action theory as internal world model t...
Distributed Multi-Agent Systems (DMAS) such as supply chains functioning in highly dynamic environments need to achieve maximum overall utility during operation. The utility from ...
Nathan Gnanasambandam, Seokcheon Lee, Soundar R. T...
The concept of a learning object (LO) has spread quickly without a very specific universal definition, and though born originally from the idea of object oriented design, with a ...