COURSES

Goals

The goal of the course is introduction into the field of computational creativity, its theory, as well as its practical aspects: tools, technologies and applications. Students learn the methodology for evaluation of the methods and results of computational creativity, recognize the limitations of computational creativity and know how to identify problems in which it is applicable. Key general methods in this research area are conceptual blending and bisociative discovery of new concepts. In addition to these, selected methods and techniques are presented that are used in specific use cases: natural language processing and language resources, data mining, data representation, use and production of semantic networks. Course aims to provide knowledge that is necessary for the independent development of new methods and applications of computational creativity in real world problems.

Curriculum

Introduction: introduction to the field of computational creativity, positioning of the field and sample applications Foundations: definitions of human and computational creativity, evaluation and metrics Methodology: computational creativity as search, bisociative knowledge discovery, concept formation and conceptual blending Resources and tools: language resources and tools for natural langugage processing (corpora, programing libraries, lexical and semantic resources), structured and textual data mining, supporting platforms for computational creativity (Clowdflows, TextFlows, Flowr, Pattern) Applications in science, health and marketing: hypothesis creation, knowledge discovery, proving mathematical axioms, food recipe creation, exercise planning, generation of slogans, acronyms and advertisements Applications in literature and art: creation of stories, metaphor, humor, poetry and paintings, composing music Summary and discussion: comparison of human and computational creativity, opportunities, limitations and ethical issues, the role of computational creativity in industry and art