On Experimenting with AgentSpeak(L) Agents Ioannis Svigkos June 2004 Harrow School of Computer Science

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

Part I: Agent Technology

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

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

Part II: BDI Agents

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

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 Theoretical Practical Practical On Experimenting with AgentSpeak(L) Agents S

Important contribution: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. On Experimenting with AgentSpeak(L) Agents AgentSpeak(L) C

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 AgentSpeak(L): Interpreter C

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

Part III: Demonstration

Building Agentspeak(L) agents Agentspeak(L) implemented in JavaAgentspeak(L) implemented in Java –Constructs: beliefs, plans, goals, intentions all accesible as APIs –Agent Interpreter –Agent Building Agentspeak(L) agents:Building Agentspeak(L) agents: –Implement BeliefsBeliefs EventsEvents Plans.Plans. On Experimenting with AgentSpeak(L) Agents

1 st Operational Cycle: -Move to Square(o)

2 nd Operational Cycle -Move to Square(o)

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

3 st Operational Cycle 4 th Operational Cycle - Move to square(p)

5 th Operational Cycle - Move to square(p)

6th Operational Cycle - Move to square(p)

7 th Operational Cycle - Drop waste into the bin

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

References M. d’Inverno and M. Luck. Engineering AgentSpeak(L): A formal computational model. Logic and Computation, 8(3), 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, M. E. Bratman, D. Israel, and M. E. Pollack, Plans and resource bounded practical reasoning. Computational Intelligence, 4:349–355, Michael Luck, Peter McBurney, Chris Preist, and Christine Guilfoyle. Agent technology: Enabling next generation computing, Augmenting BDI Agent Architectures for Social Reasoning

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, 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, 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 Springer-Verlag. Augmenting BDI Agent Architectures for Social Reasoning