Explanation-based acceleration of similarity-based learning
Proceedings of the sixth international workshop on Machine learning
Refining a relational theory with multiple faults in the concept and subconcepts
ML92 Proceedings of the ninth international workshop on Machine learning
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Learning Logical Definitions from Relations
Machine Learning
A Framework for Verbalizing Unconscious Knowledge Based on Inductive Logic Programming
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
A Learning Mechanism for Logic Programs Using Dynamically Shared Substructures
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
Constructive adaptive user interfaces: composing music based on human feelings
Eighteenth national conference on Artificial intelligence
CAUI demonstration: composing music based on human feelings
Eighteenth national conference on Artificial intelligence
Music compositional intelligence with an affective flavor
Proceedings of the 12th international conference on Intelligent user interfaces
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We often make decisions based on our feelings, which are implicit and very difficult to express as knowledge. This paper details an attempt to acquire feelings automatically. We assume that some relations or constraints exist between impressions felt and situations, which consist of an object and its environment. For example, in music arrangement, the object is a music score and its environment contains listeners, etc. Our project validates this assumption through three levels of experiments. At the first level, a program simply mimics human arrangements in order to transfer their impressions to another arrangement. This implies that the program is capable of distinguishing patterns that result in some impressions. At the second level, in order to produce a music recognition model, the program locates relations and constraints between a music score and its impressions, by which we show that machine learning techniques may provide a powerful tool for composing music and analyzing human feelings. Finally, we examine the generality of the model by modifying some arrangements to provide the subjects with a specified impression.