PRICAI '96: Topics in Artificial Intelligence

A general framework for mechanizing induction using test set.- Inductive equational reasoning.- Cost-sensitive specialization.- Efficient multiple predicate learner based on fast failure mechanism.- Acquiring user preferences for information filtering in interactive multi-media services.- The development of an interactive fault diagnosis expert system for telecommunication applications.- An intelligent education system which supports scientific thinking: Galileo - Philosophy and basic architecture.- A unified approach to handling uncertainty during cooperative consultations.- Declarative program theory with implicit implication.- Knowledge decomposition: An analysis.- The concept classification of a terminology extended by conjunction and disjunction.- Extending partial orders for sort reasoning.- An update procedure for a probabilistic deductive database.- A framework for reasoning about requirements evolution.- An application of hierarchical knowledge integration in hand-written form processing.- AMI: A model of intelligence.- Symbol processing by non-symbol processor.- Fall diagnosis using dynamic belief networks.- Remembrance of discourse based on textual continuity: A spreading activation network.- Lexical access using minimum message length encoding.- Using neural nets to investigate lexical analysis.- Validity of normality assumption in CSP research.- An improved generic arc consistency algorithm and its specializations.- High-level synthesis optimisation with genetic algorithms.- A qualitative reasoning based on an ontology of fluid systems and its evaluation.- Parallel cost-based abductive reasoning for distributed memory systems.- A history-oriented envisioning method.- Team learning of recursive languages.- Combining views on concepts in unsupervised concept learning.- The complexity of batch approaches to reduced error rule set induction.- Learning simple recursive concepts by discovering missing examples.- On semantic resolution with lemmaizing and