Perspective: Purposeful Failure in Artificial Life and Artificial Intelligence
This perspective addresses foundational challenges in AI and ALife by proposing a shift in focus from imitation of successes to failures, which could influence broad approaches in these fields.
The paper argues that studying purposeful failure, rather than success, in biological systems can provide insights for Artificial Life and Artificial Intelligence, offering an alternative to classical fitness optimization.
Complex systems fail. I argue that failures can be a blueprint characterizing living organisms and biological intelligence, a control mechanism to increase complexity in evolutionary simulations, and an alternative to classical fitness optimization. Imitating biological successes in Artificial Life and Artificial Intelligence can be misleading; imitating failures offers a path towards understanding and emulating life it in artificial systems.