Toward a Computational Theory of Evidence-Based Reasoning for Instructable Cognitive Agents

TL;DR

This paper advances a computational theory for instructable cognitive agents capable of evidence-based reasoning, demonstrated through four prototypes across critical government and public sector domains.

Contribution

It introduces a new computational framework for developing instructable cognitive agents focused on evidence-based reasoning tasks.

Findings

Four prototype agents demonstrating evidence-based reasoning

Agents successfully applied in intelligence, cybersecurity, and education

Framework supports autonomous and assistant roles in complex domains

Abstract

Evidence-based reasoning is at the core of many problem-solving and decision-making tasks in a wide variety of domains. Generalizing from the research and development of cognitive agents in several such domains, this paper presents progress toward a computational theory for the development of instructable cognitive agents for evidence-based reasoning tasks. The paper also illustrates the application of this theory to the development of four prototype cognitive agents in domains that are critical to the government and the public sector. Two agents function as cognitive assistants, one in intelligence analysis, and the other in science education. The other two agents operate autonomously, one in cybersecurity and the other in intelligence, surveillance, and reconnaissance. The paper concludes with the directions of future research on the proposed computational theory.