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A Hierarchical Agent- oriented Knowledge Model for Multi-Agent Systems Liang Xiao and Des Greer School of Computer Science, Queen's University Belfast,

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Presentation on theme: "A Hierarchical Agent- oriented Knowledge Model for Multi-Agent Systems Liang Xiao and Des Greer School of Computer Science, Queen's University Belfast,"— Presentation transcript:

1 A Hierarchical Agent- oriented Knowledge Model for Multi-Agent Systems Liang Xiao and Des Greer School of Computer Science, Queen's University Belfast, UK L.Xiao@qub.ac.uk L.Xiao@qub.ac.uk Des.Greer@qub.ac.ukDes.Greer@qub.ac.uk

2 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 2 Overview Research Aims Previous Approaches Adaptive Agent Model – Knowledge Hierarchy Modelling Knowledge in the Hierarchy Layers –Conceptual Model (Business Concepts Layer) –Fact Model (Business Concepts Layer) –Policy Rule Model (Business Rules Layer) –Reaction Rule Model (Business Rules Layer) –Business Process Rule Model (Business Processes Layer) Conclusions

3 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 3 Introduction Software must change if it is to remain useful –but changing software is expensive Reduce cost –Easy for experts to maintain business knowledge –Better still: agents manage the knowledge agents are computational entities that have dynamic behaviour, being situated in a changing environment

4 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 4 agent-oriented approaches 2 approaches –object-oriented (OO) approaches agents = active objects –agent-oriented programming (AOP) (Shoham) –agent-oriented methodology for enterprise modelling (Kendall et al) –knowledge engineering (KE) approaches agent knowledge is modelled –CommonKADS (Schreiber et al) –Agent Oriented Abstraction (Maret & Calmet) –DIAMS (Chen et al) Adaptive Agent Model –Combines both approaches

5 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 5 Why AAM? higher level of abstraction than an OO alone –knowledge can be externalised for easier management rather than fixed in objects –OO developers can reuse their skills From KE viewpoint - deployment of modelled knowledge is supported by an underpinning object layer –Extra benefits from proven technology

6 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 6 Case study Domains: –Train Running –Infrastructure Management Sub domains – Business, Incident, and Execution Examples –Infrastructure Management - Incident (IMI) Passing faults between the system and contractors –Infrastructure Management – Execution (IME) granting of isolations –Train Running - Incident (TRI), journey refinement/corrections

7 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 7 Case study continued External Entities = Train Operators, Contractors Other terms –infrastructure asset –asset faults which cause incidents which can cause track restrictions Example Requirements: –IMI-AcceptFaultReport –IMI-HandleFault –IME-ImposeSuddenRestrictions –TRI-RespondToIncident

8 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 8 Hierarchy Overview agents act and react in collaboration Inter-agent message exchanges Rules in individual agents for business tasks Reaction strategies Business Policies used in business rules vocabularies Satisfying business goals from requirements

9 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 9 Adaptive Agent Model ComponentDescription Agent  carries out activities required by AAM knowledgebase AAM knowledgebase  machine understandable, translated by agents  built from business requirements Business process  principle component of knowledgebase  involves other components, can be decomposed into sub-processes as specified in rules Business rule  statements, actions, and procedures that should be enforced in business environment  represent business requirements  refers to business concepts Business concept  atomic business units  referred by business rules, spoken by agents

10 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 10 Hierarchy Overview Business Concepts Knowledge Layer

11 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 11 Conceptual Model externalises business concepts from the applications that use them Concepts are also used to construct business rules Example from railtrack system: “fault”, “incident”, “restriction –These have properties: e.g. “fault” has properties indicating its location, impact, and priority –Register in a Conceptual Model (XML) - fault - type location impact priority

12 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 12 Model 2: Fact model For example, report about an asset fault arrives fact established that a fault has occurred in London, type “rail broken” –Create business object with appropriate values in properties Fact Manager Agent (FMA) manages all faults Policy Rule Manager Agent (PRMA) deduces new facts from existing facts by application of Policy Rules (PR) (later) Individual Agents apply Reaction Rules (RR) (later) Agent knowledge gets dynamically updated as message exchange continues and facts are added or removed lower layer class facility enables the use of an existing OO infrastructure

13 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 13 FM and CM in operation At runtime –established facts mapped to business objects instantiated from business classes (schemas in CM) –Methods invoked as required for the manipulation of facts by business rules (later) –business concepts that comprise the business rules are separate from the classes only at the time when they are used that the specific matched class methods are bound. Therefore, classes to be invoked at runtime are exchangeable and new behaviour can be achieved by the replacement of classes/ methods

14 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 14 Hierarchy Overview Business Rules Knowledge Layer

15 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 15 Policy Rule Model Policy Rule captures a constraint or invariant PR assertions on the logical relationships between entities must always be TRUE PR made up of: business objects, attributes, associations, operations PR operators: IF, THEN, AND, OR, and so on

16 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 16 Example Policy Rule If fault is located at the capital cities Then it has “immediate impact” - 100 fault.location == “London” OR “Edinburgh” OR “Cardiff” OR “Belfast” fault.impact = true 5 PR for classifying business objects

17 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 17 More Example Policy Rules If fault has “immediate impact” Then it has a high priority of 10 If fault has no “immediate impact” Then IMI-HandleFault does nothing If fault has “immediate impact” Then IMI-HandleFault establishes a new incident associated with the fault AND requests IME to place track restrictions PR deduced from attributes PR related to triggered behaviour

18 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 18 Reaction Rule Model AAM uses an event-driven agent architecture Reaction Rules represent reactive processes at individual agents (unlike PR which are run globally by the PRMA) Suppose one business domain is delegated to one agent –e.g. Infrastructure Management Incident (IMI) domain (delegation is a matter for the specification process) Agent can play different roles –e.g. IMI-HandleFault for handling faults related to Infrastructure Management Incident domain

19 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 19 REQUIREMENTS SPECIFICATION ….An asset fault is either reported to the system (Requirement: IMI-AcceptFaultReport) or detected directly by the system (Requirement: IMI- NoticeFault). The handling of both cases is the same (Requirement: IMI-HandleFault). If the fault has already been cleared no further action is needed immediately. Otherwise the system notifies the Contractor responsible for the fault and agrees a priority for fixing the fault. The fault may … Deriving Reaction Rules RECONSTRUCTED SPEC I.E REACTION RULE IMI-HandleFault is informed by IMI-AcceptFaultReport or IMI-NoticeFault about an asset fault, IF the Fault has been cleared THEN DO_NOTHING, ELSE Inform the responsible Contractor about the fault with an agreed priority, IF the fault has no immediate impact THEN DO_NOTHING, ELSE Create an incident related with the fault AND Create and put in place track restrictions using IME- ImposeSuddenRestrictions RR structure {event, processing, {condition, action} n }. Uses business objects Source of event Target for action Can be changed at any time  behaviour adaptivity

20 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 20 Reaction rule in XML - HandleFault Fault Management IMI - asset Asset - fault Fault

21 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 21 - IMI.AcceptFaultReport - - Henry - rail_broken London - 10015 rail Contractor_A …

22 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 22 asset = new Asset (reportMsg) fault = new Fault (reportMsg)

23 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 23 fault.cleared () == false - Contractor.FixFault -...

24 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 24 fault.immeImpact () == true - IME.ImposeSuddenRestrictions -... 5

25 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 25 Hierarchy Overview Business Process Knowledge Layer

26 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 26 Business Process Rule Model execution of collections of RRs (with sequence and conditions)  business processes RRs collectively constrain business processes for system goals via Business Process Rules (BPRs) RR: how one task is to be performed following a process, a goal internal to one agent BPR: how one shared business goal is achieved by a compositional process = whole collection of RRs

27 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 27 BPR “Manage New Fault” Initialising agent (IA) Either RR to initialise this BPR Final agent (FA)

28 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 28 - Manage New Fault a new fault is managed - IMI - Contractor Train Operator a new fault is reported - A Contractor will fix the fault Train Operator will re-schedule train services

29 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 29 Rule types work together. When each agent realises its responsibilities in a BPR, it applies relevant RRs and PRs. 1.fault reported to IMI. 2.“fault” structure encoded in the incoming message matches one in CM. 3.A fact about a “fault” is established in FM with its location of “London” as well as other information. 4.business object “fault” is constructed using the schema defined in CM, as well as an “asset”. 5.RR “IMI-HandleFault” is selected by IMI in this context as its section is specified to handle reported faults. 6.Facts in FM are looked for in relation with the conditions of the RR, to assist evaluation. 7.FMA interacts with PRMA and a Class Manager Agent to seek additional knowledge either by applying relevant PR or invoking related class methods. The fault is known as having impact as a result of its location, indicated by a PR (R1 in Section 4.2). 8.The business objects of “fault” and “asset” established previously are retrieved and encoded in messages. The messages are prepared to be sent to responsible agents to fix faults and impose restrictions as defined in of the RR. 9.IMI sends the message and FMA demolishes invalid facts

30 A Hierarchical Agent-oriented Knowledge Model for Multi-Agent Systems – L. Xiao, D.Greer, AOSDM, SEKE 2006 30 Conclusions Business Concepts Layer used by Adaptive Agent Model (AAM) –Conceptual Model (CM) for vocabulary –Fact Model (FM), conforming to the CM constructed at runtime by agents Business Knowledge Layer uses these concepts Reaction Rules - agent chooses a RR to react to after an event in a particular context, makes a decision, selects collaborators, and requests them to carry on the BPR. Policy Rules - while a RR is functioning, PR chains form and assist the RR to make decisions Business Process Layer –Business Process Rules dictate series of agents to react via Reaction Rules Main Contributions –Framework for building AO business models –Maintainable specification –Adaptivity

31 A Hierarchical Agent- oriented Knowledge Model for Multi-Agent Systems Liang Xiao and Des Greer School of Computer Science, Queen's University Belfast, UK L.Xiao@qub.ac.uk L.Xiao@qub.ac.uk Des.Greer@qub.ac.ukDes.Greer@qub.ac.uk


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