An Agent-Based Framework for Emergent Process Management

An Agent-Based Framework for Emergent Process Management

John Debenham
Copyright: © 2006 |Pages: 19
DOI: 10.4018/jiit.2006040103
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Emergent processes are business processes whose execution is determined by the prior knowledge of the agents involved and by the knowledge that emerges during a process instance. The amount of process knowledge that is relevant to a knowledge-driven process can be enormous and may include common-sense knowledge. If a process’ knowledge cannot be represented feasibly, then that process cannot be managed, although its execution may be supported partially. In an e-market domain, the majority of transactions, including trading orders and requests for advice and information, are knowledge-driven processes for which the knowledge base is the Internet; therefore, representing the knowledge is not at issue. Multiagent systems are an established platform for managing complex business processes. What is needed for emergent process management is an intelligent agent that is driven not by a process goal but by an inflow of knowledge, where each chunk of knowledge may be uncertain. These agents should assess the extent to which they choose to believe that the information is correct, and thus, they require an inference mechanism that can cope with information of differing integrity.

Complete Article List

Search this Journal:
Reset
Volume 20: 1 Issue (2024)
Volume 19: 1 Issue (2023)
Volume 18: 4 Issues (2022): 3 Released, 1 Forthcoming
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing