Quantitative Operational Monitoring for BDI Agents

Belief-Desire-Intention (BDI) architecture is a popular framework for designing autonomous systems. As these systems make independent decisions and execute actions independent from humans, ensuring their safety and reliability becomes a major concern. Traditional verification methods often fail to give run-time operational insights into an agent’s behaviours, especially with quantitative assessments under uncertain conditions, such as imprecise actuating. Meanwhile, BDI agents, which rely on context-sensitive subtask expansion, act as they go e.g. selecting plans at run time. To address this, we have developed a monitoring method that combines realtime operational data with probabilistic verification. This approach allows us to quantitatively analyse the decisions of BDI agents as they occur to understand the impact of each decision as it happens.

Publication Details

Journal
Research Explorer (The University of Manchester)
Published
2025-05-23
Primary Topic
AI-based Problem Solving and Planning
Type
article
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article

Quantitative Operational Monitoring for BDI Agents

Research Explorer (The University of Manchester)
AI-based Problem Solving and Planning
article

Quantitative Operational Monitoring for BDI Agents

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Abstract

Belief-Desire-Intention (BDI) architecture is a popular framework for designing autonomous systems. As these systems make independent decisions and execute actions independent from humans, ensuring their safety and reliability becomes a major concern. Traditional verification methods often fail to give run-time operational insights into an agent’s behaviours, especially with quantitative assessments under uncertain conditions, such as imprecise actuating. Meanwhile, BDI agents, which rely on context-sensitive subtask expansion, act as they go e.g. selecting plans at run time. To address this, we have developed a monitoring method that combines realtime operational data with probabilistic verification. This approach allows us to quantitatively analyse the decisions of BDI agents as they occur to understand the impact of each decision as it happens.

Research Explorer (The University of Manchester)
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AI-based Problem Solving and Planning
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Quantitative Operational Monitoring for BDI Agents · Research Explorer (The University of Manchester) (2025) | TGRS Research Map | TGRS