Artificial Intelligence

   

A Survey on Different Mechanisms to Classify Agent Behavior in a Trust Based Organic Computing Systems

Authors: Shabhrish Reddy Uddehal

Organic Computing (OC) systems vary from traditional software systems, as these systems are composed of a large number of highly interconnected and distributed subsystems. In systems like this, it is not possible to predict all possible system configurations and to plan an adequate system behavior entirely at design time. An open/decentralized desktop grid is one example, Trust mechanisms are applied on agents that show the following Self-X properties (Self-organization, Self-healing, Self-organization and so on). In this article, some mechanisms that could help in the classification of agents behavior at run time in trust-based organic computing systems are illustrated. In doing so, isolation of agents that reduce the overall systems performance is possible. Trust concept can be used on agents and then the agents will know if their interacting agents belong to the same trust community and how trustworthy are they. Trust is a significant concern in large-scale open distributed systems. Trust lies at the core of all interactions between the agents which operate in continuously varying environments. Current research leads in the area of trust in computing systems are evaluated and addressed. This article shows mechanisms discussed can successfully identify/classify groups of systems with undesired behavior.

Comments: 9 Pages.

Download: PDF

Submission history

[v1] 2019-03-08 04:47:40

Unique-IP document downloads: 24 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus