An Architecture for Hybrid Creative Reasoning

Creativity is one of the most remarkable characteristics of the human mind. It is thus natural that Artificial Intelligence’s research groups have been working towards the study and proposal of adequate computational models to creativity. Artificial creative systems are potentially effective in a wide range of artistic, architectural and engineering domains where detailed problem specification is virtually impossible and, therefore, conventional problem solving is unlikely to produce useful solutions. Moreover their study may contribute to the overall understanding of the mechanisms behind human creativity. In this text, we propose a computational hybrid architecture for creative reasoning aimed at empowering cross contributions from Case-Based Reasoning (CBR) and Evolutionary Computation (EC). The first will provide us a long-term memory, while the later will complement with its adaptive ability. The background knowledge provided by the memory mechanism can be exploited to solve problems inside the same domain or problems that imply inter-domain transfer of expertise. The architecture is the result of a synthesis work motivated by the observation that the strong similarities between the computational mechanisms used in systems developed so far could be explored. Moreover, we also propose that those mechanisms may be supported by a common knowledge representation formalism, which appears to be adequate to a considerable range of domains. Furthermore, we consider that this architecture may be explored as a unifying model for the creative process, contributing to the deepening of the theoretical foundations of the area.