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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
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Talk Outline Motivation RETSINA Infrastructure Capability-Based Coordination Middle Agents RETSINA Applications Experimental Results Conclusions
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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
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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)
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Agents Transacting in Open Environments Two phases: Locating appropriate agents –through different kinds of middle agents Performing the transaction –with or without middle agents
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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
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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
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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
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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)
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Matching Engine for Service Providers & Requesters matching capabilities with requests capability parametersservice request (LARKS) matching capabilities with requests capability parameters service request + parameters (LARKS) unsorted list of agent contact info decision algorithm sorted list of agent contact info
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Broadcaster Requester Provider 1Provider n Request for service Broadcast service request Delegation of service Results of service request Offer of service
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Yellow Page Requester Provider 1Provider n Request for service Unsorted list of contact info of (P 1,P 2, …, P k ) Advertisement of capabilities Delegation of service Results of service request
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Matchmaking MatchmakerRequester Provider 1Provider n Request for service Unsorted full description of (P 1,P 2, …, P k ) Advertisement of capabilities +para. Delegation of service Results of service request
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Classified Ads Requester 1 Provider 1 Request for service+pref. (R 1,R 2, …, R k ) contact info. Advertisement of capabilities Offer of service Service results Requester n Request for service+pref. Delegation of service Provider selects requester
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Recommender Requester Provider 1Provider n Request for service+pref. Sorted full description of (P 1,P 2, …, P k ) Advertisement of capabilities +para. Delegation of service Results of service request
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Facilitator Combines Agent Location and Transaction Phases FacilitatorRequester Provider 1Provider n Request for service+pref. Advertisement of capabilities + para. Results of service Service result Delegation of service
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Brokering BrokerRequester Provider 1Provider n Delegation of service + preferences Advertisement of capabilities + para. Delegation of service Results of service Results of service
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Contract Net ManagerRequester Provider 2Provider n Request for service + preferences Broadcast service request + pref Delegation of service Results of service Offer of service Provider 1 Broadcast Offer of service Results of Service
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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
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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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