Artificial intelligence (3rd ed.)
Artificial intelligence (3rd ed.)
Communications of the ACM
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
The algorithm design manual
Introduction to algorithms
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
Real-Time Search for Autonomous Agents and Multiagent Systems
Autonomous Agents and Multi-Agent Systems
An Event-Driven System for Distributed Multimedia Applications
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Scheduling the Supply Chain by Teams of Agents
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
Protothreads: simplifying event-driven programming of memory-constrained embedded systems
Proceedings of the 4th international conference on Embedded networked sensor systems
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
Development of an enterprise decision platform: Service-Oriented Architecture approach
International Journal of Intelligent Information and Database Systems
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
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Meta-level agents and intelligent agents in multi-agent systems can be used to search for solutions in networks and graphs where the meta-agents provide paths between nodes based on properties of the graph elements given at the time. A challenge with network problems is finding these search paths while extracting information in the network within an acceptable time bound. Moreover, this is especially difficult when information is extracted and combined from several different sources. Reducing time and making the agents work together requires a plan or an effective algorithm. In this paper we propose an approach to an event-driven algorithm that can search for information in networks using meta-agents in multi-agent systems. The metaagents monitor the agents using event-driven communication, acting as a search method and extract the searching for information in networks.