Exploring Promising Stepping Stones by Combining Novelty Search with Interactive Evolution
This addresses the challenge for evolutionary computation researchers of inefficient search processes by integrating human insight, though it is incremental as it builds on existing novelty search and interactive evolution methods.
The paper tackles the problem of objective-driven evolutionary computation often missing solutions by not resembling intermediate stepping stones, and introduces NA-IEC, which combines human intuition with novelty search to discover agent behaviors, resulting in significantly faster solutions and lower genomic complexities compared to automated methods.
The field of evolutionary computation is inspired by the achievements of natural evolution, in which there is no final objective. Yet the pursuit of objectives is ubiquitous in simulated evolution. A significant problem is that objective approaches assume that intermediate stepping stones will increasingly resemble the final objective when in fact they often do not. The consequence is that while solutions may exist, searching for such objectives may not discover them. This paper highlights the importance of leveraging human insight during search as an alternative to articulating explicit objectives. In particular, a new approach called novelty-assisted interactive evolutionary computation (NA-IEC) combines human intuition with novelty search for the first time to facilitate the serendipitous discovery of agent behaviors. In this approach, the human user directs evolution by selecting what is interesting from the on-screen population of behaviors. However, unlike in typical IEC, the user can now request that the next generation be filled with novel descendants. The experimental results demonstrate that combining human insight with novelty search finds solutions significantly faster and at lower genomic complexities than fully-automated processes, including pure novelty search, suggesting an important role for human users in the search for solutions.