Abstract. We propose a purely implicit solution to the contextual assumption generation problem in assume-guarantee reasoning. Instead of improving the L∗ algorithm — a learnin...
Yu-Fang Chen, Edmund M. Clarke, Azadeh Farzan, Min...
In this paper, we introduce IBP, an algorithm that combines g with an abstract domain model and case-based reasoning techniques to predict the outcome of case-based legal argument...
Researchers building multi-agent algorithms typically work with abstracted away from real applications. The abstracted problem instances allow systematic and detailed investigatio...
Paul Scerri, Pragnesh Jay Modi, Wei-Min Shen, Mili...
The concept of diversity was successfully introduced for recommender-systems. By displaying results that are not only similar to a target problem but also diverse among themselves,...
Product recommender systems are a popular application and research field of CBR for several years now. However, almost all CBRbased recommender systems are not case-based in the or...