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RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support

RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support The Robotics Institute Carnegie Mellon University PI: Katia Sycara http://www.cs.cmu.edu/~sycara http://www.cs.cmu.edu/~softagents Talk Outline Motivation RETSINA Infrastructure

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RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support

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  1. RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support The Robotics Institute Carnegie Mellon University PI: Katia Sycara http://www.cs.cmu.edu/~sycara http://www.cs.cmu.edu/~softagents

  2. Talk Outline • Motivation • RETSINA Infrastructure • Capability-Based Coordination • Middle Agents • RETSINA Applications • Experimental Results • Conclusions

  3. Features of MAS • Multiple agents through communication networks • Local views - no agent has sufficient information or capabilities to solve problems alone • Decentralized control - no “master agent” • Decentralized data - no global data storage • Agent Coupling - balancing computation and communication • Asynchronous - multiple activities operating in parallel

  4. Basic Problems of Multi-Agent Systems • Coordination in an open environment • Asynchronous agent operation • Distributed resource allocation • Distribution of tasks • Interoperability of agents • Privacy concerns • Persistent goal-directed behavior • Overall system stability • Conflicts (resolution, avoidance)

  5. Agents Transacting in Open Environments Two phases: • Locating appropriate agents • through different kinds of middle agents • Performing the transaction • with or without middle agents

  6. Issues with Locating Agents (1) • Evaluation criteria • performance • robustness • scalability • load balancing • privacy • Where the matching is done • At the requester (preserving the privacy of requesters) • middle agents • service providers

  7. Issues with Locating Agents (2) • Information needed to feed the “matching engine” • Requester can provide request for service, with or without service-related preferences (e.g., cost, quality) • Output • Unsorted list of contact info • Sorted list of contact info • given to requester provider • Input kept at middle agent to be fed into transaction phase

  8. Transaction Phase • Providers and requesters interact with each other directly • a negotiation phase to find out service parameters and preferences (if not taken into account in the locating phase) • delegation of service • Providers and requesters interact through middle agents • middle agent finds provider and delegates • hybrid protocols • Reasons for interacting through middle agents • privacy issues (anonymization of requesters and providers) • trust issues (enforcement of honesty; not necessarily keep anonymity of principals); e.g. NetBill

  9. Protocols • Who to talk to: principals involved • Message content: • ex: a LARKS specification • Local processing: • ex: implied by KQML performatives (service-request, request-for-service-providers)

  10. Matching Engine for Service Providers & Requesters sorted list of agent contact info unsorted list of agent contact info decision algorithm matching capabilities with requests (LARKS) matching capabilities with requests (LARKS) service request + parameters service request capability parameters capability parameters

  11. Broadcaster Request for service Requester Broadcaster Broadcast service request Offer of service Delegation of service Results of service request Provider 1 Provider n

  12. Yellow Page Request for service Requester Yellow Page Unsorted list of contact info of (P1,P2, …, Pk) Advertisement of capabilities Delegation of service Results of service request Provider 1 Provider n

  13. Matchmaking Request for service Requester Matchmaker Unsorted full description of (P1,P2, …, Pk) Advertisement of capabilities +para. Delegation of service Results of service request Provider 1 Provider n

  14. Classified Ads Requester 1 Request for service+pref. Classified Ads Request for service+pref. Advertisement of capabilities (R1,R2, …, Rk) contact info. Requester n Offer of service Provider selects requester Delegation of service Provider 1 Service results

  15. Recommender Request for service+pref. Requester Recommender Sorted full description of (P1,P2, …, Pk) Advertisement of capabilities +para. Delegation of service Results of service request Provider 1 Provider n

  16. FacilitatorCombines Agent Location and Transaction Phases Request for service+pref. Requester Facilitator Results of service Advertisement of capabilities + para. Service result Delegation of service Provider 1 Provider n

  17. Brokering Delegation of service + preferences Requester Broker Results of service Advertisement of capabilities + para. Delegation of service Results of service Provider 1 Provider n

  18. Contract Net Request for service + preferences Requester Manager Results of service Delegation of service Broadcast service request + pref Broadcast Results of Service Offer of service Broadcast Offer of service Provider 1 Provider 2 Provider n

  19. Motivation for Multi Agent Systems • Global Information and Markets • Increasingly networked world • Vast quantities of unorganized information • Diverse and distributed information sources • Moving from locating documents to making decisions

  20. Conclusions • Agent-based software development is an emerging paradigm • Agent societies that parallel human societies • Agent society as a unit of intelligence • Implications of agent societies for human workplace and institutions • Challenges • Overall system (humans + agents) predictability • Integration of legacy systems • Security, privacy and trust issues

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