The Unified Modeling Language user guide
The Unified Modeling Language user guide
The unified software development process
The unified software development process
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Calculating optimal decision using meta-level agents for multi-agents in networks
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Integrating Web Services and Intelligent Agents in Supply Chain for Securing Sensitive Messages
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Applying Multi-Agent System Technique to Production Planning in Order to Automate Decisions
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Comparing ontologies using multi-agent system and knowledge base
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
A multi-agent system with negotiation agents for e-trading products and services
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part IV
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In order to coordinate and deliver information in the right time and to the right place, theories from multi-agent systems and information logistics are combined. We use agents to support supply chain by searching for company specific information. Hence, there are a vast number of agents working at the Internet, simultaneously, which requires supervising agents. In this paper, we suggest using meta-agents to control the behaviour of a number of intelligent agents, where the meta-agents are working with coordination of the communication that takes place in a supply chain system. As an example, we look at a manufacturing company receiving orders on items from customers, which need to be produced. The handling of this distributed information flow can be thought of as an Information Logistics Processes and the similarities of the functioning of processes and intelligent agents' behaviour are illuminated.