activity
20232025
most citedImproving Knowledge Extraction from LLMs for Task Learning through Agent Analysis

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2025

Requirements for Aligned, Dynamic Resolution of Conflicts in Operational Constraints

Steven J. Jones, Robert E. Wray, John E. Laird

Deployed, autonomous AI systems must often evaluate multiple plausible courses of action (extended sequences of behavior) in novel or under-specified contexts. Despite extensive tr…

cs.AI2025★ 1 cited

Applying Cognitive Design Patterns to General LLM Agents

Robert E. Wray, James R. Kirk, John E. Laird

One goal of AI (and AGI) is to identify and understand specific mechanisms and representations sufficient for general intelligence. Often, this work manifests in research focused o…

cs.AI2025

Requirements for Recognition and Rapid Response to Unfamiliar Events Outside of Agent Design Scope

Robert E. Wray, Steven J. Jones, John E. Laird

Regardless of past learning, an agent in an open world will face unfamiliar events outside of prior experience, existing models, or policies. Further, the agent will sometimes lack…

cs.AI2024

Eliciting Problem Specifications via Large Language Models

Robert E. Wray, James R. Kirk, John E. Laird

Cognitive systems generally require a human to translate a problem definition into some specification that the cognitive system can use to attempt to solve the problem or perform t…

cs.AI2023

Exploiting Language Models as a Source of Knowledge for Cognitive Agents

James R. Kirk, Robert E. Wray, John E. Laird

Large language models (LLMs) provide capabilities far beyond sentence completion, including question answering, summarization, and natural-language inference. While many of these c…

cs.AI2023★ 3 cited

Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis

James R. Kirk, Robert E. Wray, Peter Lindes +1

Large language models (LLMs) offer significant promise as a knowledge source for task learning. Prompt engineering has been shown to be effective for eliciting knowledge from an LL…