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Application of Agent- Oriented Techniques to Network Supervision Babak Esfandiari, Mitel Corporation
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Different opportunities for agents in networks n Routing n Network Management u Network Supervision u GDMO/CMIS u TMN
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Network Supervision Problematic n Fault detection n Alarm filtering and qualification n Multiple and cascading faults n...
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Existing attempts n Mostly use of expert systems for diagnosis ([Gaiti] [Garijo]…) u Use of agent-oriented architectures (?) u Revealed the importance of explicit representation of Time u No high-level communication between network management platforms u Acquisition of expertise is still a bottleneck
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Chronicles Chronicle RobotLoadMachine { event (Robot: (outRoom, inRoom), e1); event (Robot: (inRoom, outRoom), e4); event (MachineInput: (unLoaded, loaded), e2); event (Machine: (Stopped, Running), e1); e1 < e2; 1’ <= e3 - e2 <= 6’; 3’ <= e4 - e2 <= 5’; hold (Machine: Running, (e2, e2)); hold (SafetyConditions: True, (e1, e4)); when recognized {report “Successful load”;} }
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Some theoretical speculations: Agents and OSI layers n Using Newell’s Knowledge Level as the highest communication layer? u Expressing applications behaviors in “rational” terms (Beliefs, Desires, Intentions, …) u Communicating such terms using high-level interaction languages (KIF/KQML?) and protocols
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Interface Agents “A program that […] provides assistance to a user dealing with a particular application. Such agents learn by watching over the shoulder of the user and detecting patterns and regularities…” (Maes)
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The Assistant’s structure
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Use of BDI to specify the agent’s behavior n Trust as a modal operator n B(a,f) Λ Trusts(a,b,f) -> K(a,f) n Trusts(a,a,f) ? n Trusts(a,human operator,*) n Trusts(a,b,f) with b := other agent ?
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Learnability of chronicles: a set of Oracles n PASSIVE: supplies events and actions n PASSIVE S : PASSIVE + no overlapping n ACTIVE MQ : {events}+action -> yes/no n ACTIVE EQ :chronicle ->yes/(no+example)
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Learnability of chronicles: Results n With one chronicle per action: u positive with PASSIVE S u positive with ACTIVE MQ + PASSIVE n If more than one chronicle per action: u negative with any oracle Ô Difficulties: Ô overlapping Ô x chronicles/action Ô where find such oracles ?
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The Learning System 3 steps: n Chronicle creation n Chronicle evaluation n Chronicle confirmation
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An example (1) Evaluation of: a b c -> Unconfirmed chronicle base: 1: a b c d -> Trust: 1 2: a b c e -> Trust: 1 3: a b c f -> Trust: 2 Confirmed chronicle base: 1: a b c g -> Trust: 3
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An example (2) Unconfirmed chronicle base: 1: d -> Trust: 1 2: e -> Trust: 1 3: a b c f -> Trust: 2 Confirmed chronicle base: 1: a b c g -> Trust: 3 2: a b c -> Trust: 3
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MAGENTA: MAnaGEmeNT Application or Multi-AGENT Assistant ? ObjectManager: processes the query CommunicationManager: sends and receives messages EventManager: triggers event notifications Management Application: processes the events and publishes queries
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Experimentation n The local network n Transpac data n Robot behavior pattern detection n Help to a Smalltalk programmer n Overlapping management n Collaborative learning
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Results
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Finding other oracles: Collaborative assistance Presentation protocol Matchmaking protocol Query protocol
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Conclusion and perspectives n Summary: u Use of Interface Agents in Network Supervision F Theoretical results on chronicle learning F Appropriate algorithms u Use of Network Management standards to build an Agent Development platform n Next: u Improve the algorithms (first order, partial order) u Big scale experimentation u Other applications of MAGENTA: remote programming, distributed debugging,...
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