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Can we make it real? When we have solved the ”AI problem”... But we don’t need to A computer can play a fair game of chess Agents may (should) address specific tasks
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Software Agents &Agent-Based Systems
Sverker JansonIntelligent Systems LaboratorySwedish Institute of Computer [email protected]
A somewhat trite vision...
Intelligent agents...• understand what we mean• find and use relevant
information• automate routine tasks• adapt to our needs and
desires• cooperate with other
assistants• et c, et c
Cf. Knowledge Navigator ’87, featuring Phil
Can we make it real?
• When we have solved the ”AI problem” ...
• But we don’t need to• A computer can play
a fair game of chess• Agents may (should)
address specific tasks
Common characteristics...
Agents are...• situated• autonomous• reactive• pro-active• social• rational• et c, et c
Cf. Jennings, Sycara, Wooldridge, A Roadmap of Agent Research and Development, JAAMAS, 1998
Commonmetaphore?
Agent-based systems
Systems & informationintegration Multiagent
systems
ResourcemarketsInternetcommerceRecommendersystems
Software agents
Agents
Assistant agents
Believable agents
Simulated agents
Economics
People...
Sociology
Robots
Mobile agents
Artificial life
Personal assistant agents
• Reducing work and information overload
• Examples– Apple’s Knowledge
Navigator– MIT Media Lab
(various) – Microsoft Paper Clip– Office of Naval
Research Tactical Picture Agent
Mobile agents
• Moving running software between computers
• Purpose– overcome network latency
(e.g. interact in real time)– use located resources
(e.g. computing power, storage, special hardware)
– see e.g. Seven Good Reasons for Mobile Agents by Lange and Oshima, CACM 3(42)
• Problems– Security, trust,
performance
Mobile agents, unique selling point…
Agent-based systems
How communicate?
• Sharing information & bridging data models
• High level speech act based protocols– KQML / FIPA ACL– Cf. SOAP
• Expressive logic based content formats– KIF / FIPA SL– Cf. semantic web
• Systems and information integration
TELL p(a)
How coordinate?
• Coordinating different interests and goals
• Agent: locus of self-interest
• Market based interaction– Contract net– Combinatorial markets
• Combination with organization– Coalition formation
• Multiagent systems, e.g. automated markets
Objects vs agents
• Objects– state– methods– control– method invocation
• Agents– goals– knowledge– planning– negotiation
Agents address software complexity• Complex functionality?
– “mechanistic” explanation too complex?
– replace direct manipulation with dialogue
– from understanding to trust
– Cf. assistant agents
• Complex interrelationships?– let components be
“selfish”– interaction through
negotiation– global properties by
mechanism design– Cf. agent-based systems
Whose agent?
