The capacity of combinational creativity---i.e., when novel ideas are produced through unfamiliar combinations of familiar ideas---is difficult to recreate computationally. In particular, it is a hard task for autonomous computational systems to tackle the combinatorial explosion of potential combinations, and to be capable of recognizing the value of newly created ideas (concepts, theories, solutions, etc.), particularly when they are not specifically sought ---this is the problem of creative serendipitous behaviour.In this project, we aim to develop a computationally feasible, cognitively-inspired formal model of concept invention, drawing on Fauconnier and Turner's theory of conceptual blending, and grounding it on a sound mathematical theory of concepts. Conceptual blending, although successfully applied to describing combinational creativity in a varied number of fields, has hardly been used for implementing creative computational systems, mainly due to the lack of sufficiently precise mathematical characterizations thereof.The model to be defined in the context of this project will be based on Goguen's proposal of a Unified Concept Theory, and will draw from interdisciplinary research results from cognitive science, artificial intelligence, formal methods and computational creativity. To validate our model, we will implement a proof of concept of an autonomous computational creative system that will be evaluated by humans in two testbed scenarios: mathematical reasoning and melodic harmonization.We envisage that the results of this project will be highly significant for gaining a deeper scientific understanding of creativity, for fostering the synergy between understanding and enhancing human creativity, and for developing new technologies for autonomous creative systems.