Prof. Ken Forbus Ph.D

Walter P. Murphy Professor of Computer Science and Professor of Education at Northwestern University

Talk title: "Creative Support Companions: Some Ideas"

Abstract: An exciting opportunity for AI is the development of intelligent assistants that, working with people, enable them to do far more than they can alone. What would that mean for creative activities? This talk explores some ideas for using the Companion cognitive architecture to create software collaborators that support creative work. Companions include human-like analogical processing, facilities for natural language and sketch understanding, and rich relational representations that capture aspects of human visual, spatial, and conceptual knowledge. For supporting creative activities, this should enable them to (1) help suggest and explore cross-domain analogies, (2) interact via natural modalities, providing higher communication bandwidth and reducing friction compared to software tools, and (3) adapt to their human partners over time, building up a portfolio of joint work that can be drawn upon in future efforts.


Dr. Marco Schorlemmer

from the Artificial Intelligence Research Institute (IIIA-CSIC), Barcelona, Spain

Talk title: "Reasoning at a Distance by Way of Conceptual Metaphors and Blends"

Abstract: Cognitive scientists of the embodied cognition tradition have been providing evidence that a large part of our creative reasoning and problem-solving processes are carried out by means of conceptual metaphor and blending, grounded on our bodily experience with the world. In this talk I shall aim at fleshing out a mathematical model that has been proposed in the last decades for expressing and exploring conceptual metaphor and blending with greater precision than has previously been done. In particular, I shall focus on the notion of ‘aptness’ of a metaphor or blend and on the validity of metaphorical entailment. Towards this end, I shall use a generalisation of the category-theoretic notion of ‘colimit’ for modelling conceptual metaphor and blending in combination with the idea of ‘reasoning at a distance’ as modelled in the Barwise-Seligman theory of information flow. I shall illustrate the adequacy of the proposed model with an example of creative reasoning about space and time for solving a classical brain-teaser. Furthermore, I shall argue for the potential applicability of such mathematical model for ontology engineering, computational creativity, and problem-solving in general.


Prof. Bipin Indurkhya, Ph.D

Computer Science & Cognitive Science Dep., Jagiellonian University, Kraków, Poland

Talk title: "Thinking Like A Child: The Role of Surface Similarities in Stimulating Creativity"

Abstract: An oft-touted mantra for creativity is: think like a child. We focus on one particular aspect of child-like thinking here, namely surface similarities. Developmental psychology has convincingly demonstrated, time and again, that younger children use surface similarities for categorization and related tasks; only as they grow older they start to consider functional and structural similarities. We consider examples of puzzles, research on creative problem solving, and two of our recent empirical studies to demonstrate how surface similarities can stimulate creative thinking. We examine the implications of this approach for designing creativity-support systems.


Dr. Andrew Lovett

from the Northwestern University, US.

Talk title: "Modeling visual problem-solving as analogical reasoning."

Abstract: Visual problem-solving tasks are powerful tools for evaluating intelligence and creative thinking in humans. For example, the Raven’s Progressive Matrices is one of the best single-test predictors of a person’s spatial, verbal, and mathematical ability. To better understand the skills that allow people to succeed at problem-solving, I have developed a computational model. The model builds on the claim that analogical reasoning lies at the heart of visual problem-solving. Images are compared via structure-mapping, aligning the common relational structure in two images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model re-represents them to facilitate the comparison. In this talk, I describe what the model has taught me, in terms of the challenges faced during problem-solving and the skills that can be used to overcome those challenges.


Professor Lledó Museros

from Universitat Jaume I, Castellón, Spain

Talk title: "Creating and rating harmonic colour palettes for a given style"

Abstract: Colour, and more specifically, colour harmony has an important role in creativity and design. During the talk a qualitative colour theory, and the operations to create harmonic colour palettes, will be presented. Then the process to classify these palettes as a life-style, as for instance casual, romantic, elegant, and so on will be introduced. Moreover, the palettes generated can be rated in function of the taste of the people by using social data. On the other hand, how these information can be used to characterise images, and also to give emotional descriptors to the images will be presented.


Dr. Tarek R. Besold

from the Digital Media Lab, Center for Computing and Communication Technologies (TZI), Universitat Bremen, Germany.

Talk title: "Symbolic models and computational properties of constructive reasoning in cognition and creativity"

Abstract: Analogy is one of the most studied forms of non-classical reasoning working across different domains, usually taken to play a crucial role in creative thought and problem-solving. In the first part of the talk, I will introduce general principles of computational analogy models (relying on a generalisation-based approach to analogy-making). We will then have a closer look at Heuristic-Driven Theory Projection (HDTP) as an example for a theoretical framework and implemented system: HDTP computes analogical relations and inferences for domains which are represented using many-sorted first-order logic languages, applying a restricted form of higher-order anti-unification for finding shared structural elements common to both domains. The presentation of the framework will be followed by a few reflections on the "cognitive plausibility" of the approach motivated by theoretical complexity and tractability considerations. In the second part I will touch upon several applications of HDTP to modeling important cognitive capacities, including concept blending processes as current "hot topic" in Cognitive Science.