Modeling Creativity by Tom De Smedt

What we call human creativity is the conceptual ability to be innovative, to combine existing objects and concepts in new ways, for new purposes. This is often a trial-and-error process, with the actual original idea often emerging as a side effect from something else. Consider how the immensely popular Post-It notes actually emerged from a research trying to develop an extremely strong glue. Creativity is not limited to art, it is merely our word for finding innovative solutions. Artificial creativity tries to mimic this heuristic process in algorithmic terms. It is an attempt to model creativity using computer programs. Artificial creativity is closely related to what is called emergence in the field of Artificial Intelligence. Emergent behaviour arises when a number of simple entities interact and subsequently exhibit more complex (often unexpected) behaviour as a group. Think about ants: a single ant has little or no intelligent or creative capacities. It follows trails of scent and nothing much more. But as a collective, the ant colony is capable of solving complex problems creatively, from finding the shortest path to food to mobilising army, maintaining and herding caterpillars. If you observe ant colonies in bird's eye view, they almost look like a computer network. Artificial creativity can be compared to an ant colony: a number of simple algorithms (or agents) working together, sharing and distributing information in the hope of developing emergent behaviour to solve new and unexpected problems.