Knowledge transfer between expert and novice agents is a challenging problem given that the knowledge representation and learning algorithms used by the novice learner can be fund...
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
We present a general framework for studying heuristics for planning in the belief space. Earlier work has focused on giving implementations of heuristics that work well on benchma...
We propose a general framework for multi-context reasoning which allows us to combine arbitrary monotonic and nonmonotonic logics. Nonmonotonic bridge rules are used to specify th...
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are P 2 hard. To overc...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...