Toward Life-Long Creative Problem Solving: Using World Models for Increased Performance in Novelty Resolution
Creative problem solving (CPS) is a skill which enables innovation, often times through repeated exploration of an agent’s world. In this work, we investigate methods for life-long creative problem solving (LLCPS), with the goal of increasing CPS capability over time. We de- velop two world models to facilitate LLCPS which use sub-symbolic action and object information to predict symbolic meta-outcomes of actions. We experiment with three CPS scenarios run sequentially and in sim- ulation. Results suggest that LLCPS is possible through the use of a world model, which can be trained on CPS exploration trials, and used to guide future CPS explo- ration.