Sensemaking in Novel Environments: How Human Cognition Can Inform Artificial Agents
This addresses the challenge of building AI agents that can interpret unfamiliar situations, though it appears incremental as it builds on existing cognitive and AI concepts.
The paper tackles the problem of enabling artificial agents to make sense of novel environments by proposing a unified conceptual framework for sensemaking, which involves sharing and recombining attributes across memories to create synthesized signs.
One of the most vital cognitive skills to possess is the ability to make sense of objects, events, and situations in the world. In the current paper, we offer an approach for creating artificially intelligent agents with the capacity for sensemaking in novel environments. Objectives: to present several key ideas: (1) a novel unified conceptual framework for sensemaking (which includes the existence of sign relations embedded within and across frames); (2) interaction among various content-addressable, distributed-knowledge structures via shared attributes (whose net response would represent a synthesized object, event, or situation serving as a sign for sensemaking in a novel environment). Findings: we suggest that attributes across memories can be shared and recombined in novel ways to create synthesized signs, which can denote certain outcomes in novel environments (i.e., sensemaking).