Work

Assessing Model Proficiency in Autonomous Agents: A Signal Processing Perspective

Year: 2025

Type: conference-paper

Abstract: Autonomous agents play a crucial role in applications such as emergency response and urban security, where they are often required to operate independently in critical situations without direct human supervision. A key aspect of autonomy is the agent’s ability to assess its proficiency in carrying out tasks and making decisions based on this assessment. This paper introduces a state-space model to present a novel framework for assessing the proficiency of autonomous agents. The proposed metric is based on statistical model assessment, enabling agents to evaluate their model performance in real-time. More specifically, we focus on the proficiency of the model used for measurement predictions. We validate the effectiveness of our metric through simulations with synthetic data. Future work will explore the potential of this framework to enhance decision-making accuracy and improve task performance.

Source: IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)

DOI: 10.1109/icasspw65056.2025.11011249

Authors: A. Guerra, F. Guidi, D. Dardari, P. M. Djurić

Institutions: University of Bologna, Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, Stony Brook University

Language: English

Topic: Target Tracking and Data Fusion in Sensor Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

OpenAlex ID: W4410770838

FWCI:

Cites: 18

Cited by:

Related to: 10