Toward creative problem solving agents: Action discovery through behavior babbling
Creative problem solving (CPS) is the process by which an agent discovers unknown information about itself and its environment, allowing it to accomplish a previously impossible goal. We propose a framework for CPS by robots for discovering novel actions via behavior babbling, capable of learning a representation of novel actions at both a symbolic planning level, and a sub-symbolic action controller level. Our framework employs two modes of discovery – a focused incubation method that scopes its search to the actions and entities composing the failed plan, and a defocused incubation method which enables exploration of actions and entities outside of the failed plan. We implemented and tested our framework using a Baxter robot in a 3D physics-based simulation environment, where we ran three proof-of-concept object manipulation scenarios. Results suggest that it is possible to use behavior babbling as a method for the autonomous discovery of flexible and reusable actions.