An introduction to agents
DARTS 2003 – Session 2A – 22nd October 2003
Joris Maervoet and Stijn Bernaer
KaHo Sint-Lieven Hogeschool, Ghent
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
1 – Agent definitions
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)
PropertiesRe-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
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
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
Agents and objects, what’s the difference?
Agent A Agent B
Object A Object Bmethod
ACL messag
e
2 - Agent applications: 2 examples
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
The battle at Helm's Deep
“making realistic crowds is making realistic individuals”
Taken from: Pierre Vinet/ New Line Productions
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
The battle at Helm's Deep
Taken from: Entertainment Weekly’s EW.com
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
http://technology.arc.nasa.gov
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
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
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
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
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
3 – Agent applications: overview
Source: Agentlink Roadmap
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
• 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
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
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
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
4 - Agent-oriented design
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
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
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
5 – Programming agents
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
JADE and LEAP
• JADE: still in development. (last: 3.0)
• LEAP: project recently taken over by JADE
Huge number of successful applications
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
JADE and LEAP
Taken from: LEAP User Guide
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.
6 - The AMobe-project
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)
‘97 – ’99 OCAPIObjeCt georiënteerde Agenten voor gedistribueerde PlannIngssystemen: using agents to optimize rosters and the routes of mobile nurses
‘99 – ‘01 COALACOoperating And Learning Agents: creating an ontology for planning systems, Semantic Web
‘01 – ‘03 CoFfTeAComponent Framework for Timetabling Applications: component-based framework for timetabling applications
‘02 – ‘04 AMobeApplication 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 – ’05 DINGODIstributed Negotiation - Gedistribueerde Onderhandeling
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
??Mobile devices
AMobe
Technology Platform
Architecture
Functionality
uLinux – Palm OS Epoc32 – Windows CE
J2ME – WabaLEAP – JIAC IV
Permanent presenceMobile positioning …
Software patternsOth
er
fact
ors
pricemarket situation
dimensions …
2.5G: GPRS - EDGE WLAN - bluetooth3G: UMTS
Case studies
Tele Atlas
• geographical database, employees on location
T&I
• Mobile devices assist people with non-congenital brain injuries
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
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
UPLOADCLIENT AGENT
RECEIVING SLAVE AGENT
SENDING SLAVE AGENT
SERVERDB
AGENT
CLIENTDB
AGENT
POLICY AGENTPOLICY AGENTPOLICY AGENT
DBDB
Server (ev. DB server) Server (ev. synchro server)
Mobiel toestelIN
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FA
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AG
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SK
AG
EN
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INFO
RM
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RECEIVING SLAVE AGENT
RECEIVING SLAVE AGENT
SENDING SLAVE AGENT
SENDING SLAVE AGENT
Server Mobile device
arno.txt
*GML*GML*GML …
blixa
arno panamarenkocaesargaudi
spartacus(x)
spartacus(x).txt
*GML*GML*GML …
ToSend.txt
*GML*GML*GML …
caesar.cltStart/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
Create I am active
Demo in JADE
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)