This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Significant increase in collected data for investigative tasks and the increased complexity of the reasoning process itself have made investigative analytical tasks more challengi...
Abstract. Constraint Satisfaction has been widely used to model static combinatorial problems. However, many AI problems are dynamic and take place in a distributed environment, i....
The use of approximation as a method for dealing with complex problems is a fundamental research issue in Knowledge Representation. Using approximation in symbolic AI is not strai...
While it has been realized for quite some time within AI that abduction is a general model of explanation for a variety of tasks, there have been no empirical investigations into ...