# APIA: An Architecture for Policy-Aware Intentional Agents

arXiv: https://arxiv.org/abs/2109.08287 · HTML: https://mlsanity.com/paper/2109.08287/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2021.

## Built on by (most cited first, 4 of 4)

- [An ASP Framework for the Refinement of Authorization and Obligation Policies](https://mlsanity.com/paper/2305.13190/) (2023)
- [Autonomous Agents and Policy Compliance: A Framework for Reasoning About Penalties](https://mlsanity.com/paper/2512.03931/) (2025)
- [Architecture for Simulating Behavior Mode Changes in Norm-Aware Autonomous Agents](https://mlsanity.com/paper/2502.09215/) (2025)
- [Explainability Framework for Policy-Aware Autonomous Agents](https://mlsanity.com/paper/2607.21209/) (2026)

## Abstract (arXiv)

This paper introduces the APIA architecture for policy-aware intentional agents. These agents, acting in changing environments, are driven by intentions and yet abide by domain-relevant policies. This work leverages the AIA architecture for intention-driven intelligent agents by Blount, Gelfond, and Balduccini. It expands AIA with notions of policy compliance for authorization and obligation policies specified in the language AOPL by Gelfond and Lobo. APIA introduces various agent behavior modes, corresponding to different levels of adherence to policies. APIA reasoning tasks are reduced to computing answer sets using the Clingo solver and its Python API.