Abstract
Conventional evaluation methods for autonomous agents may prioritize task completion without assessing an agent's ability to handle systemic discrepancies between its instructions and its operational environment. A dynamic evaluation framework is described that can assess an agent's cognitive resilience. The framework may operate by introducing controlled inconsistencies, for example, planted traps, into a sandboxed environment, which can create a conflict between the agent's instructional data and the runtime reality. The system can then evaluate the agent's response, focusing on its ability to detect the discrepancy, classify its root cause, and propose a structural resolution rather than focusing on task completion. This methodology provides a structured approach that may be used to quantify an agent's reasoning and problem-solving skills in dynamic environments.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Leimgruber, Isaac and Zimmermann, Nicolas, "Evaluating Agent Cognitive Resilience Using Controlled Environmental Inconsistencies", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10368