Understanding accountability in contract violations, e.g., whom is accountable for what, is a tedious, time-consuming, and costly task for human decision-making, especially when contractual responsibilities are delegated among parties. Intelligent software agents equipped with expert capabilities such as monitoring and diagnosis help save time and improve accuracy of diagnosis by formal reasoning upon electronic contracts. Such contracts are represented as commitment norms, a well studied artifact in multi-agent systems, which provide semantics for agent interactions. Due to the open and heterogeneous nature of multi-agent systems, commitments are often violated. When a commitment is violated, e.g., an exception occurs, agents need to collaborate to understand what went wrong and which agent is responsible. We propose Comodo: a framework for monitoring commitment delegations and detecting violations. We define a complete set of possible rational delegation schemes for commitments, identifying for each combination of delegations what critical situations may lead to an improper delegation and potentially to a commitment violation. Comodo provides a sound and complete distributed reasoning procedure that is able to find all improper delegations of a given commitment. We provide the complete implementation of Comodo using the Reactive Event Calculus, and present an e-commerce case study to demonstrate its workings. Due to its generic nature, we discuss the application of our approach to other distributed diagnosis problems in emergency healthcare, Internet of Things and smart environments, and security, privacy, and accountability in the context of socio-technical systems.

Comodo : Collaborative monitoring of commitment delegations / Kafalı, Özgür; Torroni, Paolo. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - STAMPA. - 105:(2018), pp. 144-158. [10.1016/j.eswa.2018.03.057]

Comodo : Collaborative monitoring of commitment delegations

KAFALI, REMZI OZGUR
;
Torroni, Paolo
2018

Abstract

Understanding accountability in contract violations, e.g., whom is accountable for what, is a tedious, time-consuming, and costly task for human decision-making, especially when contractual responsibilities are delegated among parties. Intelligent software agents equipped with expert capabilities such as monitoring and diagnosis help save time and improve accuracy of diagnosis by formal reasoning upon electronic contracts. Such contracts are represented as commitment norms, a well studied artifact in multi-agent systems, which provide semantics for agent interactions. Due to the open and heterogeneous nature of multi-agent systems, commitments are often violated. When a commitment is violated, e.g., an exception occurs, agents need to collaborate to understand what went wrong and which agent is responsible. We propose Comodo: a framework for monitoring commitment delegations and detecting violations. We define a complete set of possible rational delegation schemes for commitments, identifying for each combination of delegations what critical situations may lead to an improper delegation and potentially to a commitment violation. Comodo provides a sound and complete distributed reasoning procedure that is able to find all improper delegations of a given commitment. We provide the complete implementation of Comodo using the Reactive Event Calculus, and present an e-commerce case study to demonstrate its workings. Due to its generic nature, we discuss the application of our approach to other distributed diagnosis problems in emergency healthcare, Internet of Things and smart environments, and security, privacy, and accountability in the context of socio-technical systems.
2018
Comodo : Collaborative monitoring of commitment delegations / Kafalı, Özgür; Torroni, Paolo. - In: EXPERT SYSTEMS WITH APPLICATIONS. - ISSN 0957-4174. - STAMPA. - 105:(2018), pp. 144-158. [10.1016/j.eswa.2018.03.057]
Kafalı, Özgür; Torroni, Paolo
File in questo prodotto:
File Dimensione Formato  
Comodo-ESWA-2018.pdf

accesso aperto

Tipo: Postprint
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 552.27 kB
Formato Adobe PDF
552.27 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/634619
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 7
social impact