In this paper I am presenting a model of human communication which allows a decomposition of our subjective experience into units called strategies. Strategies are systematically ordered sequencesof representations in our sensory modalities, endowed with so called submodality distinctions, orientation, effect, and links to other representations. As certain people prove more successful in performing given tasks than others, we want to model their strategies and transfer them to other intelligent agents. Unlike most philosophers who have written about qualia and believe that subjective experience condemns us to "solitary confinement," I believe strategies are accessible to us. Here is how. All behavior, from learning to communication and change, is the result of our strategies. It is constantly giving us information about the underlying strategies by way of physiologicaland linguistic cues. The model I am presenting in this paper offers a systematic study and categorization of these cues...

Serendipity, the faculty of making fortunate and unexpected discoveries by accident, is recognized today as playing a key role in sparking innovation. It does not seem, however, to be manageable by any means, which has kept it as a relatively unexplored subject of research. This paper claims that, although it may not be possible to program serendipity, it is quite possible to program for serendipity, that is, to induce serendipitous insights through the use of computers.

This paper presents Dr. Divago, which is a system that aims at getting musical and drawing ideas by searching for solutions in a multi-domain knowledge base. Its main goal is to achieve successful transfer of ideas between any two different domains, relying on procedures inspired on metaphor interpretation theories to establish bridges of conceptual correspondences. This system is currently under development and this paper presents a general outline of what are and will be its main components.

This paper presents Darwinci, a system that generates new ideas, using a multi-domain knowledge base composed by musical and drawing structures. Its theoretical background comes from the theory of Divergent Production as stated in [7], Genetic Algorithms and metaphor interpretation. Rather than attempting to model human thought, Darwincis main goal is to make cross-domain transfer of ideas, in order to create something new, thus becoming a good proposal for creative problem solving.

This paper presents Darwinci, a system that generates new ideas, using a multi-domain knowledge base composed by musical and drawing structures. Its theoretical background comes from the theory of Divergent Production as stated in [7], Genetic Algorithms and metaphor interpretation. Rather than attempting to model human thought, Darwincis main goal is to make cross-domain transfer of ideas, in order to create something new, thus becoming a good proposal for creative problem solving.

Analogical problem solving with visual representations is important in many situations. I propose to develop a computational theory of visual analogy that will 1) support the notion that visual abstractions are useful for analogical transfer in cases where there are symbolic mismatches at the non-visual level, and 2) provide a language of primitives that will prove useful for visually representing problems and problem solving procedures. Support for these endeavors will come from how the theory predicts and explains test data, comparison with published experimental participant data, comparison to non-visual accounts, implementation of the theory in a computer program, and experiments with it.

Transformational creativity requires a change of the search space. As such, Evolutionary Computation (EC) approaches are incapable of transformational creativity. In this paper, we discuss how canonical EC techniques can be extended in order to yield the potential of transformational creativity. We present a formalized description of how this can be attained, and the experimental results achieved with a metaevolutionary scheme.

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