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Monitoring compliance with E-contracts and norms

Monitoring compliance with E-contracts and norms The behaviour of autonomous agents may deviate from that deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent’s behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper, we propose a general framework for observation of agents’ behaviour, and recognition of this behaviour as constituting, or counting as, compliance or violation. The framework deploys monitors that receive inputs from trusted observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation of the framework, and its deployment in electronic contracting environments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence and Law Springer Journals

Monitoring compliance with E-contracts and norms

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Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer Science+Business Media Dordrecht
Subject
Computer Science; Artificial Intelligence (incl. Robotics); International IT and Media Law, Intellectual Property Law; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
ISSN
0924-8463
eISSN
1572-8382
DOI
10.1007/s10506-015-9167-9
Publisher site
See Article on Publisher Site

Abstract

The behaviour of autonomous agents may deviate from that deemed to be for the good of the societal systems of which they are a part. Norms have therefore been proposed as a means to regulate agent behaviours in open and dynamic systems, where these norms specify the obliged, permitted and prohibited behaviours of agents. Regulation can effectively be achieved through use of enforcement mechanisms that result in a net loss of utility for an agent in cases where the agent’s behaviour fails to comply with the norms. Recognition of compliance is thus crucial for achieving regulation. In this paper, we propose a general framework for observation of agents’ behaviour, and recognition of this behaviour as constituting, or counting as, compliance or violation. The framework deploys monitors that receive inputs from trusted observers, and processes these inputs together with transition network representations of individual norms. In this way, monitors determine the fulfillment or violation status of norms. The paper also describes a proof of concept implementation of the framework, and its deployment in electronic contracting environments.

Journal

Artificial Intelligence and Law – Springer Journals

Published: Jul 9, 2015

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