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On Experimenting with AgentSpeak(L) Agents

On Experimenting with AgentSpeak(L) Agents. Harrow School of Computer Science. June 2004. Ioannis Svigkos svigkoi@westminster.ac.uk. O v e r v i e w. Part I: Agent Technology. Part II: BDI Agents. AgentSpeak(L). Agentspeak(L) constructs Agentspeak(L) Interpreter Limitations. Part III:

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On Experimenting with AgentSpeak(L) Agents

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  1. On Experimenting with AgentSpeak(L) Agents Harrow School of Computer Science June 2004 Ioannis Svigkossvigkoi@westminster.ac.uk

  2. O v e r v i e w • Part I: • Agent Technology. • Part II: • BDI Agents. • AgentSpeak(L). • Agentspeak(L) constructs • Agentspeak(L) Interpreter • Limitations. • Part III: • Demonstraing AgentSpeak(L) S On Experimenting with AgentSpeak(L) Agents 1/22

  3. Part I: Agent Technology

  4. Software Systems • Computing environments: • Applications • Information • Components are dispersed • Networking technologies • Information • Increases in size, many forms • Unstructured, altered without notice • Future of computing • Autonomic, Pro-active, Ubiquitous, Pervasive … a solution can be … N On Experimenting with AgentSpeak(L) Agents .

  5. .. Agent Technology • An Agent is …. • Dimensions • Autonomy • Situated-ness • Responsive-ness • Proactive-ness • Social ability … a particular kind of agents … N On Experimenting with AgentSpeak(L) Agents

  6. Part II: BDI Agents

  7. ... BDI Agents • Decision making model based: • Human Practical reasoning • Includes two processes: • Deliberation • Means-end Reasoning • BDI: • Belief, Desire Intention Model … But why BDI agents ? C On Experimenting with AgentSpeak(L) Agents

  8. BDI Agents • Why BDI model: • Description based on “mentalistic” attributes. • “Humanistic” way to predict agent behaviour. • A “re-usable” abstract model. • Reactive and deliberative approach. • Research outcome • Theoretical • Practical S On Experimenting with AgentSpeak(L) Agents

  9. .... AgentSpeak(L) • Important contribution: • Represents a large family of BDI systems. • An approach to bridge the gap between theory and practice. • Abstraction of successful implemented systems PRS and dMars. C On Experimenting with AgentSpeak(L) Agents

  10. .... AgentSpeak(L) • Event: Perceivable characteristics • External • Internal • Beliefs: Knowledge about the world • Plan Library: Procedural Knowledge • Intentions: Partial Instantiate Plans • Actions: Selected for execution • Select plan • Select Event • Select intention On Experimenting with AgentSpeak(L) Agents

  11. ..... AgentSpeak(L): Interpreter C On Experimenting with AgentSpeak(L) Agents

  12. ...... AgentSpeak(L): Limitations • Selection functions are non-deterministic • Programming of only single agent systems. • A goal can be achieved, if an agent: • Has the necessary plans • Can perform all actions in a plan. • It cannot handle plan failure • Events cannot be “processed” are not removed. • Not aware about lack of procedural knowledge • Redundant computation On Experimenting with AgentSpeak(L) Agents

  13. Part III: Demonstration

  14. Building Agentspeak(L) agents • Agentspeak(L) implemented in Java • Constructs: beliefs, plans, goals, intentions all accesible as APIs • Agent Interpreter • Agent • Building Agentspeak(L) agents: • Implement • Beliefs • Events • Plans. On Experimenting with AgentSpeak(L) Agents

  15. 1st Operational Cycle: • Move to Square(o)

  16. 2nd Operational Cycle • Move to Square(o)

  17. 3rd Operational Cycle Tom knowns there is a waste at square(o)

  18. 3st Operational Cycle 4th Operational Cycle - Move to bin @ square(p)

  19. 5th Operational Cycle - Move to bin @ square(p)

  20. 6th Operational Cycle - Move to bin @ square(p)

  21. 7th Operational Cycle - Drop waste into the bin

  22. 6st Operational Cycle 8th Operational Cycle Observe the environment for any changes.

  23. ................ References • M. d’Inverno and M. Luck. Engineering AgentSpeak(L): A formal computational model. Logic and Computation, 8(3), 1998. • N. R. Jennings, K. Sycara, and M. Wooldridge. A roadmap of agent research and development. Journal of Autonomous Agents and Multi-Agent Systems, 1(1):7–38, 1998. • M. E. Bratman, D. Israel, and M. E. Pollack, Plans and resource bounded practical reasoning. Computational Intelligence, 4:349–355, 1988. • Michael Luck, Peter McBurney, Chris Preist, and Christine Guilfoyle. Agent technology: Enabling next generation computing, 2003. Augmenting BDI Agent Architectures for Social Reasoning

  24. ................ References • Anand S. Rao. Agentspeak(l): BDI agents speak out in a logical computable language. In Modelling Autonomous Agents in a Multi-Agent World, pages 42–55, 1996. • Jaime Simao Sichman, Rosaria Conte, Yves Demazeau, and Christiano Castelfranchi. A social reasoning mechanism based on dependence networks. In Michael N. Huhns and Munundar P. Singh, editors, Readings in Agents, pages 416–420, San Francisco, 1997. Morgan Kaufmann. • M. Wooldridge and N. R. Jennings. Agent Theories, Architectures, and Languages: A Survey. In Jennings Wooldridge, editor, Intelligent Agents, ECAI-94, workshop on Agent theories, Architectures, and Languages (ATAL), number 890 in LNAI, pages 1–39, Berlin, Germany, August 1994. Springer-Verlag. Augmenting BDI Agent Architectures for Social Reasoning

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