We propose a new method to control memory resources by static analysis. For this, we introduce the notion of sup-interpretation which bounds from above the size of function outputs...
Abstract. We propose that traditional case-based recommender systems can be improved by informing them with context data describing the user's environment. We outline existing...
Abstract. The problem of defining robot behaviors to completely address a large and complex set of situations is very challenging. We present an approach for robot's action se...
Case Retrieval Networks (CRNs) facilitate flexible and efficient retrieval in Case-Based Reasoning (CBR) systems. While CRNs scale up well to handle large numbers of cases in the c...
Sutanu Chakraborti, Robert Lothian, Nirmalie Wirat...
Abstract. We show how case bases can be compiled into Decision Diagrams, which represent the cases with reduced redundancy. Numerous computations can be performed efficiently on th...
Abstract. The contents of the case knowledge container is critical to the performance of case-based classification systems. However the knowledge engineer is given little support i...
The design of a CBR system involves the use of similarity metrics. For many applications, various functions can be adopted to compare case features and to aggregate them into a glo...
In this paper we present TransUCP, a general framework for transformational analogy. Using our framework we demonstrate that transformational analogy does not meet a crucial condit...
Ambient Intelligence is a research area that has gained a lot of attention in recent years. One of the most important issues for ambient intelligent systems is to perceive the envi...
The present paper describes a case-based reasoning solution for solving the task of selecting adequate templates for realizing messages describing actions in a given domain. This s...