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Seminar SS 09 Organic Computing

Seminar SS 09 Organic Computing. Supervisor: Thomas Ebi Chair for Embedded Systems (CES) University of Karlsruhe. What is Organic Computing?. Merriam Webster Dictionary on „organic“: of, relating to, or derived from living organisms

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Seminar SS 09 Organic Computing

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  1. Seminar SS 09Organic Computing Supervisor: Thomas Ebi Chair for Embedded Systems (CES) University of Karlsruhe

  2. What is Organic Computing? Merriam Webster Dictionary on „organic“: • of, relating to, or derived from living organisms • having the characteristics of an organism : developing in the manner of a living plant or animalLearning from nature • forming an integral element of a whole • having systematic coordination of parts The whole is more than the sum of its parts

  3. What is Organic Computing? • Self-X Properties (“Autonomic Computing” IBM) • Self-Organization • Self-Configuration • Self-Optimization • Self-Healing • Self-Protection

  4. Swarm Intelligence • Collective behavior in decentralized, self-organized systems • Particle Swarm Optimization • Ant Colony Algorithm [ M Dorigo (Hrsg). Ant colony optimization and swarm intelligence. 5th International Workshop, ANTS (2006) ] [ RC Eberhart, Y Shi. Particle Swarm Optimization: Developments, Applications and Resources. CEC (2001). ] [ V Maniezzo, A Carbonaro. Ant Colony Optimization: an Overview. Essays and Surveys in Metaheuristics (2001). ] [ P Svenson et al. Swarm Intelligence for logistics: Background. Technical report (2004).]

  5. Multi-Agent Systems • Autonomous acting entities (agents) working together to reach a given goal [ M Wiering et al. Learning in Multi-Agent Sytems. (2000). ] [ L Panait, S Luke. Cooperative Multi-Agent Learning: The State of the Art. (2005). ] [ M Wooldridge. An Introductionto Multiagent Systems. John WileyandSons Ltd (2002). ] [ MS Greenberg et al. Mobile Agentsand Security. (1998) . ]

  6. Evolutionary Algorithms • Four major paradigms • Genetic Algorithms • Genetic Programming • Evolutionary Programming • Evolutionary Strategies [ Darrell Whitley. An Overview of Evolutionary Algorithms: Practical Issues and Common Pitfalls. (2001). ] [ PJ Fleming, RC Purshouse. Evolutionary algorithms in control systems engineering: a survey. Control Engineering Practice 10:1223–1241 (2002). ]

  7. Topics • Organic Computing Overview • ACE: Agent-based Computational Economics • AutoNomos: Distributed Approach to Organizing Large Systems of Mobile Objects (Hovering Data Clouds) • Smart teams: Local Distributed Strategies for Self-Organizing Robotic Exploration Teams • ASoC: Architecture and Design Methodology for Automatic Systems on Chip

  8. Literature Research • Reading paper references • Search engines, e.g. Google, Yahoo, and so on • Wikipedia • Not to be referenced in the paper • Paper search engine http://scholar.google.com • University library • Journal papers via “Elektronische Zeitschiftenbibliothek” • Portals • ACM • IEEE Xplore • DBLP

  9. Paper and Presentation • Paper • LaTeX and Word Templates • 10 pages • In German or English • Correct scientific writing (structure, references, …) • typos, duplicate words, … are avoidable • Presentation • 30 minutes • Projector is available  PowerPoint, OpenOffice, PDF

  10. Dates and Deadlines • July 25 End of lectures • July 20 Presentation II • July 20 Presentation I • July 13 Slides have to be finished • June 29 Preliminary final version of slides • June 22 Paper has to finished • June 15 Preliminary final version of paper • May 25 First version of paper • May 11 Structure of paper • May 4 First ideas, read papers

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