In this paper we revisit the trade-off between adaptation and retrieval effort traditionally held as a principle in case-based reasoning. This principle states that the time needed...
Abstract. In this paper we present a method for supplementing incomplete cases with information from other cases within a case base. The acquisition of complete and correct cases i...
Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help use...
Abstract. When learning by observing an expert, cases can be automatically generated in an inexpensive manner. However, since this is a passive method of learning the observer has ...
This paper presents a new approach for spatial event prediction that combines a value function approximation algorithm and case-based reasoning predictors. Each of these predictors...
Case-based planning (CBP) systems are based on the idea of reusing past successful plans for solving new problems. Previous research has shown the ability of meta-reasoning approac...
In forestry, it is important to be able to accurately determine the volume of timber in a harvesting site and the products that could potentially be produced from that timber. We d...
Conor Nugent, Derek G. Bridge, Glen Murphy, Bernt-...
Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performanc...
A model-free, case-based learning and control algorithm called S-learning is described as implemented in a simulation of a light-seeking mobile robot. S-learning demonstrated learn...