An Approach to Event-Driven Algorithm for Intelligent Agents in Multi-agent Systems

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.

[1]  Hans-Jürgen Appelrath,et al.  Scheduling the supply chain by teams of agents , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[2]  Ronald L. Hartung,et al.  Using Meta-agents for Multi-agents in Networks , 2007, IC-AI.

[3]  Cristina D. Ururahy,et al.  Event-Driven Programming for Distributed Multimedia Applications , 2009 .

[4]  R. Prim.  Shortest connection networks and some generalizations , 1957 .

[5]  Michael R. Genesereth,et al.  Software agents , 1994, CACM.

[6]  Clifford Stein,et al.  Introduction to Algorithms, 2nd edition. , 2001 .

[7]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[8]  J. Kruskal.  On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .

[9]  Patrick Henry Winston,et al.  Artificial intelligence (3rd ed.) , 1992 .

[10]  Roberto Ierusalimschy,et al.  An event-driven system for distributed multimedia applications , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[11]  Lonnie R. Welch,et al.  Meta-reasoning for a distributed agent architecture , 2001, Proceedings of the 33rd Southeastern Symposium on System Theory (Cat. No.01EX460).

[12]  M. Birkner,et al.  Blow-up of semilinear PDE's at the critical dimension. A probabilistic approach , 2002 .

[13]  Lakhmi C. Jain,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2004, Lecture Notes in Computer Science.

[14]  George Luger,et al.  Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition) , 2004 .

[15]  Ronald L. Hartung,et al.  Calculating Optimal Decision Using Meta-level Agents for Multi-Agents in Networks , 2007, KES.

[16]  Jerome L. Paul,et al.  Algorithms: Sequential, Parallel, and Distributed , 2004 .

[17]  Steven Skiena,et al.  The Algorithm Design Manual , 2020, Texts in Computer Science.

[18]  Muneeb Ali,et al.  Protothreads: simplifying event-driven programming of memory-constrained embedded systems , 2006, SenSys '06.

[19]  Toru Ishida,et al.  Real-Time Search for Autonomous Agents and Multiagent Systems , 1998, Autonomous Agents and Multi-Agent Systems.

[20]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[21]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .