Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring
Published in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025
Recommended citation: Bravo-Rocca, G., et al. (2025). "Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring." International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Detroit, USA. https://dl.acm.org/doi/10.5555/3709347.3743552
This paper presents an adaptive cognitive architecture for interpretable machine learning monitoring in agent systems. The work was accepted at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2025 in Detroit, USA. Preprint available on arXiv and as PDF.
Recommended citation: Bravo-Rocca, G., et al. (2025). “Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring.” International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Detroit, USA.