1. An introduction to agents DARTS 2003 – Session 2A – 22nd October 2003 Joris Maervoet and Stijn Bernaer KaHo Sint-Lieven Hogeschool, Ghent

2. Talk outline An introduction to agents 1.Agent definitions 2.Agent applications: Helm’s Deep/NASA 3.Agent applications: overview 4.Agent-oriented design 5.Programming agents 6.The AMobe project

3. 1 – Agent definitions

4. Agent definition Encapsulated computer system, situated in some environment, and capable of flexible autonomous action in that environment in order to meet its design objectives (Jennings) Agent interaction is inevitable to achieve individual objectives and to manage inter-dependencies (Jennings)

5. Properties Re-active On external asynchronous stimuli Autonomous Controls own actions, operates without direct intervention of others Pro-active Goal directed, takes initiatives Continuous and persistent Is “living”, not “running” Social Communicates with other agents and humans Learning Adaptiveness based on experience Mobile Moves among machines in network

6. Why Agents? Load reduction Trusted Agent travels between server and client, carries safe protocol Delay independence Agents perform in real time, not over uncertain networks Protocols Agents encapsulate protocols, for better adaptability and maintainability Asynchronous Together with autonomy, agents can act on their own, without necessity for continuous interaction

7. Why Agents? Adaptive Agents react autonomously on changes in the environment Heterogeneity Distributed systems are heterogeneous in nature. Agents are optimal for system integration Robustness Mobile agents can make a distributed system more robust and fault tolerant by deciding autonomously in case of an error

8. Agents and objects, what’s the difference? Agent AAgent B Object AObject B method  ACL message

9. 2 - Agent applications: 2 examples

11. The battle at Helm's Deep Gathering 70,000 people, dressing them and choreographing each other is out of question Stephen Regelous created Massive (special-effects program) Massive is able to generate characters with their own minds (also called agents) Source: Wired News, Digital actors in Rings can think

12. The battle at Helm's Deep “making realistic crowds is making realistic individuals” Taken from: Pierre Vinet/ New Line Productions

13. The battle at Helm's Deep Agent’s brains (look like complex flow charts) define how they see and hear, how fast they run, … Agent’s movements are based on these of stunt actors to allow for example realistic ducks to avoid a sword Like real people, agents are influenced by their environment

14. The battle at Helm's Deep Taken from: Entertainment Weekly’s EW.com

15. The battle at Helm's Deep Each agent makes subtle responses to its surroundings with fuzzy logic rather than yes/no decisions Placing agents into a simulation, each agent makes decisions from it’s point of view (no crowd control) Other examples: generating flocks of birds, duplicating film stars

16. http://technology.arc.nasa.gov

17. NASA Traditionally ground systems deal with spacecraft planning & scheduling, establishment of communications and (in some cases) processing So the ground system is responsible for managing the spacecraft and its activities (remote control) Source: Nasa Ames Research Center, Remote Agent Project Website

18. Remote Agent The first artificial intelligence control system to control a spacecraft without human supervision Remote Agent successfully demonstrated the ability to plan onboard activities and correctly diagnose and respond to simulated faults in spacecraft components

19. Remote Agent Advantages Faster reactions to problem situations (getting instructions from Earth could take a while) Less operation costs and less remote control:the Remote agent can take care of itself and does not need a hundred of specialised people on board or on the ground

20. Remote Agent Made up of 3 components Planner and scheduler (PS): produces flexible plans, specifying the basic activities that must take place in order to accomplish the mission goals Smart executive (EXEC): carries out the planned activities Mode Identification and Recovery (MIR): monitors the health of the spacecraft and attempts to correct any problems that occur

21. Remote Agent These components work together and communicate to ensure that the spacecraft accomplishes the goals of the mission Taken from: Nasa Ames Research Center, Remote Agent Project Website

22. 3 – Agent applications: overview Source: Agentlink Roadmap

23. Agent-based systems - overview Assistant agents: e.g. TAC, where agents book hotels and make travel arrangements Multi-agent decision systems: e.g. components in a network may jointly seek to allocate scarce resources of the network Multi-agent simulation systems: used to model some complex real-world domains, e.g. biological populations

24. Manufacturing eCommerce e.g. Telecommunications Supply chain management Entertainment and leisure e.g. “The Creature Games”, SimCity the film “The Two Towers” Industrial and Commercial Applications

25. Simulation applications Agent-based simulation characterised by Agent-based computing Social sciences: studies interaction among social entities and include social psychology, management, policy and some areas of biology Computer simulation: techniques such as discrete event, object-oriented, equation-based simulation

26. Simulation applications Advantages Forecasting some complex real-world environments (economy, society, biology) Examples Flight Simulators: train pilots to respond appropriately to unexpected events Southwest Airlines increased revenues by $ 10 million dollar by using a agent-based simulation of cargo routing

27. Application opportunities Ambient intelligence: providing an environment of thousands of embedded and mobile devices interacting to support user- centred goals and activity Bioinformatics Grid computing: geographically separated computers that share applications, data and computational resources Electronic business

28. 4 - Agent-oriented design

29. A new software paradigm procedures  data types  objects  agents Point of view: a further powerful abstraction, a new software paradigm Methodologies (e.g. AUML) in development Agent patterns

30. Pitfalls (Jennings) Political: you oversell agents, you get dogmatic about agents Management: you don’t know why you want to use agents, you want generic solutions to one- off problems Conceptual: you believe agent technology is a ‘silver bullet’, you forget that you are developing software, you forget agents are multi-threaded software

31. Pitfalls (Jennings) Analysis and design: you ignore related technology, you don’t exploit concurrency, you start from a tabula rasa Agent level: you want your own architecture, you use too much AI / no AI Society level: you see agents everywhere, you have too few/many agents, you spend all the time on an infrastructure, your agents interact too freely, your system lacks structure

32. 5 – Programming agents

33. JADE and LEAP Java Agent Development framework (JADE) is an agent development environment implemented in J2SE. Developing FIPA-compliant (Foundation for Intelligent Physical Agents) agent applications for ‘interoperable intelligent multi-agent systems’. Lightweight Extensible Agent Platform (LEAP) replaces JADE’s ‘core functionality’ for devices with low memory/CPU capacities. JADE-based agentplatform which is standardized for mobile devices and compatible with mobile Java environments

34. JADE and LEAP JADE: still in development. (last: 3.0) LEAP: project recently taken over by JADE Huge number of successful applications

35. JADE and LEAP JADE’s functionality Distributed agentplatform on several JVM’s, behaviour model, AMS (automatische (de)registratie) – DF – ACC. GUI Debugging tools … Intraplatform mobility Multiple DF ACL messages, several protocols Interface for external applications

36. JADE and LEAP Taken from: LEAP User Guide

37. JADE and LEAP LEAP on Symbian OS devices: PersonalJava. LEAP on PocketPC devices : install CLDC/MIDP or PersonalJava. LEAP on Palm OS: install CLDC/MIDP. LEAP (or just JADE) on Windows NT/98/2000/XP: install J2SE.

38. 6 - The AMobe-project

39. IT research group Department of Engineering at KaHo Sint- Lieven Hogeschool Research areas: personnel scheduling, agent technology, timetabling, mobile devices, optimisation, artificial intelligence Funded projects (IWT)

40. ‘97 – ’99OCAPI ObjeCt georiënteerde Agenten voor gedistribueerde PlannIngssystemen : using agents to optimize rosters and the routes of mobile nurses ‘99 – ‘01COALA COoperating And Learning Agents: creating an ontology for planning systems, Semantic Web ‘01 – ‘03CoFfTeA Component Framework for Timetabling Applications: component-based framework for timetabling applications ‘02 – ‘04AMobe Application Development for Mobile Devices: agent-oriented software- development on mobile devices ‘02 – ‘04 TITAN (internal project) Developing a timetabling application for the Engineering department ‘03 – ’05DINGO DIstributed Negotiation - Gedistribueerde Onderhandeling

41. AMobe Application Development for Mobile Devices 2 coordinators, 2 researchers How are mobile devices integrated in applications? 2 case studies (evaluation and iteration) Website: http://ingenieur.kahosl.be/projecten/AMobe

42. ?? Mobile devices AMobe TechnologyPlatform Architecture Functionality uLinux – Palm OS Epoc32 – Windows CE J2ME – Waba LEAP – JIAC IV Permanent presence Mobile positioning … Software patterns Other factors price market situation dimensions … 2.5G: GPRS - EDGE WLAN - bluetooth 3G: UMTS

43. Case studies Tele Atlas geographical database, employees on location T&I Mobile devices assist people with non- congenital brain injuries

44. Framework for efficient datatransfer First case study gained interest: IDEWE and WGK have similar cases Common agent-construction for efficient datatransfer between server and mobile devices Why agents? Agents can decide at which moment which data will be sent. Agents enable loosely coupled software development

45. SYNCHRO AGENT ToestelID|TransactieID|prio|richting|aanvrager|DBactie ---------+------------+----+--------+---------+------- 002 | 927 |form| -> |dca002@… | get… 002 | 928 |form| <- |uca002@… |hereis… 003 | 929 |form| -> | pol9@… |hereis… 003 | 930 |form| <- | pol5@… | get… # actieve transacties prioriteitsdrempel DOWN- LOAD CLIENT AGENT UPLOAD CLIENT AGENT RECEIVING SLAVE AGENT SENDING SLAVE AGENT SERVER DB AGENT CLIENT DB AGENT POLICY AGENT DB Server (ev. DB server)Server (ev. synchro server) Mobiel toestel INTERFACE AG. TASK AGENTS INFORMATION AGENTS RECEIVING SLAVE AGENT SENDING SLAVE AGENT

46. ServerMobile device arno.txt *GML*GML* GML … blixa arnopanamarenkocaesargaudi spartacus(x) spartacus(x).txt *GML*GML*GM L … ToSend.txt *GML*GML*G ML … caesar.clt Start/stop Fill Watch size Copy arno.txt Could I send a report? Spartacus(x) will be your partner Please send everything end Fill Watch Force blixa CreateI am active Demo in JADE

47. Demo: agents over GPRS Purchase: Sierra Wireless AirCard 750 (PCMCIA cf. PenPCs Tele Atlas) + Mobistar abonnement voor GPRS First test: JADE agent on portable (with GPRS - link) communicates with JADE agent on server within our LAN (both Windows XP)