The paper titled Regulatory Services to Automate Compliance with Ex-post Enforcement by Lu-Chi Liu, Mostafa Mohajeri Parizi, Thomas van Binsbergen, and Tom van Engers was accepted at AICOL 2022: AI Approaches to the Complexity of Legal Systems.
Abstract:
Software systems are expected to comply with norms from a variety of sources. However, the increasing volume and the dynamism of norms make it rather difficult to have a fully compliant software system by design. This paper proposes a generic architecture of regulated software systems that facilitates compliance with high-level policies through regulatory services. Our architectural model has the flexibility to adapt to norm modifications and to norm violations by including ex-post enforcement mechanisms. The proposed solution is assessed using a case study and a prototype implementation in the eFLINT and ASC2 languages for modeling norms and software/social agents respectively.
Lu-Chi Liu
PhD Candidate
I am a PhD student in the Complex Cyber Infrastructure (CCI) group. I come from Taiwan and have my master’s degree in Computer Science at National Taiwan University. After that, I worked in the software industry as a DevOps engineer for about two years and decided to persue a doctoral degree abroad. Being supervised by Tom van Engers and L.Thomas van Binsbergen, my research focuses on the implementation of digital enforceable contracts, investigating blockchain, smart contracts, compliance, governance, normative systems, adversarial settings, etc. I will be working on the SSPDDP project which aims to create secure, scalable and policy-enforced environment for data exchange. Apart from this, I like to play volleyball, watch Netflix series, taste delicious food and attend various activities in my free time!
Mostafa Mohajeri Parizi
PhD Candidate
L. Thomas van Binsbergen
Assistant Professor
Tom van Engers
Full Professor (FDR)
I conduct research on AI & Law, with a particular focus on normative reasoning. Having a track record in AI & Law research going back to 1983, I have worked both on knowledge-driven as well as data-driven AI approaches.