Leveraging Conflict to Bridge Cognitive Reasoning and Generative Algorithms

Abstract

Autonomous agents require the ability to identify and adapt to unexpected conditions. Real-world environments are rarely stationary, making it problematic for agents operating in such environments to learn efficient policies. There is therefore a need for a general framework capable of detecting when an agent has encountered novel conditions, and determining how it should adjust its actions. In this position paper we propose a framework that couples cognitive reasoning and generative algorithms by leveraging conflict detection to adjust to unexpected dynamics. Specifically, we propose that a metacognitive conflict resolution mechanism is necessary; such a mechanism would balance the use of commonsense and deliberative reasoning to allow the agent to navigate novel conditions.