1. A Goal-Based Organizational Perspective on Multi-Agent Architectures Manuel Kolp mkolp@cs.toronto.edu http://www.cs.toronto.edu/km/tropos Department of Computer Science University of Toronto M5S 3G4 Toronto, Canada NATO Meeting - May 23 2001, Québec, Canada

2. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 2 Motivation Narrowing the gap requirements between architectures Multi-Agent systems are organizations of coordinated and autonomous agents. Same concepts for requirements and architectures –Multi-Agents architecture as organization and intentional structures –Coordinated autonomous components with goals to fulfil and social inter-dependencies ( i* ) –Concepts from organization theory and modeling Ontology: 3 levels (Macro, micro, atomic) Part of TROPOS (http://www.cs.toronto.edu/km/tropos)

3. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 3 Software Agent –Implemented with/in software technologies –Environment : humans, machines, other software agents, platforms. Multi-agent system: organization of individuals to achieve particular, possible common goals. An Organizational Computing Paradigm Agent : Agent : Individual who can act –Autonomous, pro- active, goal, knowledge oriented, adaptative Intelligence with/in its environment  Intelligence

4. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 4 Agent Individual Characteristics Autonomous Autonomous –is capable acting without direct external intervention. –It has some degree of control over its internal state and actions based on its own experiences. Mobile Mobile –able to transport itself from one environment to another. Unpredictable Unpredictable –able to act in ways that are not fully predictable, even if all the initial conditions are known. It is capable of non deterministic behavior. Rugged Rugged –able to deal with errors and incomplete data robustly.

5. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 5 Agent Organizational Characteristics Interactive Interactive –communicates with the environment and other agents. Adaptive Adaptive –capable of responding to other agents and/or its environment. Sociable Sociable –may act on behalf of someone or something, that is, acting in the interest of, as a representative of, or for the benefit of some entity. Proactive Proactive –goal-oriented, purposeful. It does not simply react to the environment.

6. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 6 Agent Organizational Characteristics Coordinative Coordinative –able to perform some activity in a shared environment with other agents. Coordination via plans or other process management mechanism. Cooperative Cooperative –able to coordinate with other agents to achieve a common purpose; non antagonistic agents that succeed or fail together. Competitive Competitive –able to coordinate with other agents except that the success of one agent implies the failure of others (>< cooperative).

7. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 7 The BDI Agent Model Intelligence for Agent Intelligence for Agent –State is formalized by knowledge (i.e., beliefs, goals, plans, assumptions) and interacts with other agents with symbolic language –Able to choose an action based on internal goals and the knowledge that a particular action will bring it closer to its goals. The Belief-Desire-Intention The Belief-Desire-Intention (BDI) agent model has its roots in philosophy and cognitive science. –An agent has beliefs about the world and desires to satisfy, driving it to form intentions to act. –An intention is a commitment to perform a plan. –Beliefs, desires and intentions : the mental attitudes (or mental states) of an agent.

8. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 8 Inside the BDI Model Human Beliefs - perceived understanding of the world Goals or desires Accumulated behaviours Belief, Desire, Intentions Agent Beliefs - database of perceived world knowledge Execution Engine Goals or desires Pre-compiled plans Intentions - currently executing plans

9. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 9 Agents at Work Contextual Beliefs New Beliefs/Facts Goal/Desire/Need Running Plan/Intention

10. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 10 i*: an Organizational Modeling Framework Goals are relative, fulfillment is collaborative

11. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 11 The Strategic Dependency Model social dependencies Focus on social dependencies among actors rather than only actor goals, actions etc. goalstasksresources Actors have goals, need tasks be carried out and resources to be made available; social & intentional relationships Dependencies define social & intentional relationships among actors, where one actor depends on another to satisfy a goal or satisfice a softgoal, execute a process or furnish a resource; Dependencies can be goal dependencies, task dependencies, resource dependencies or soft goal dependencies Softgoals more qualitative Softgoals are distinguished from goals because they do not have a formal definition, and are amenable to a different (more qualitative) kind of analysis (not well-defined).

12. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 12 Four Kinds of Dependencies Goal Task Resource Softgoal Media Shop

13. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 13 Softgoals Functional goals, such as “Handle Customers Orders” : well defined goals in the sense that they admit a formal definition. Not all goals are functional. “Increase Market Share”, “Happy Customers” or “Easily Adaptable System” : qualities that the software system should adhere to. softgoals Non functional Goals: softgoals, “fuzzy goals” (clouds) with no clearcut criteria for satisfaction; satisficed Hence softgoals are satisficed, not satisfied. How well the system accomplishes its functions

14. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 14 A Formal Framework  Precise Semantics Entity Order Has orderId: Number, cust: Customer, date: Date, tems: SetOf [MediaItem] Entity MediaItem Has itemId: Number, itemTitle: String, description: Text, editor: String … Actor Customer Has customerId: Number, name: Name, address: Address, tel: PhoneNumber, … Capable of MakeOrder, Pay, Browse, … Goal  order:Order  buy:BuyMediaItems[order] (order.cust=self   Fulfil(buy)) Actor MediaShop Has name: {MediaLive}, address: {“735 Yonge Street”}, phone#: 0461-762-883 Capable of Sell, Ship, SendInvoice, … Goal  ms:IncreaseMarketShare(Fulfil(ms)) GoalDependency BuyMediaItems Mode Fulfil Has order: Order Defined ItemsReceivedOK(order) Depender Customer Dependee MediaShop Necessary Fulfil( PlaceOrder(order)) SoftGoalDependency IncreaseMarketShare Mode Maintain Depender MediaShop Dependee Customer Necessary  cust:Customer  place:PlaceOrder[order] (order.cust=cust )   Fulfil(place)) Action MakeOrder Performed By Customer Refines PlaceOrder Input cust : Customer, date : Date, items : SetOf [MediaItem] Output order : Order Post order.cust = cust  order.date = date  order.items  items

15. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 15 Strategic Rationale Model Graph with four main types of nodes -- goal, task, resource, and softgoal -- and two main types of links -- means-ends links and process decomposition links. Describes the criteria in terms of which each actor selects among alternative dependency configurations. Means-ends Means-ends relate goals to tasks that can satisfy these goals: “Given goal (end) G, how can I decompose it (means) in order to find a way to fulfill it”. Task decomposition Task decomposition links relate tasks to other component tasks Tasks can also be decomposed to goals.

16. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 16 Rationale View of an Actor

17. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 17 A User 2 On-line Buying System Media taxonomy –on-line catalog –DBMS E-Shopping Cart –Check In –Buying –Check Out Search Engine –catalog browser –Keywords –full-text Secure –$ transactions –orders Multimedia –description –samples

18. Operational Context of the System Operational Context of the System Functionsqualities environment Functions and qualities for the system within its environment ”Organizational Map”

19. The System as A Social Actor Medi@ ”Rationale Map”

20. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 20 The NFR framework : Building Goals Models To arrive at a more qualitative framework for modeling goals, we also need to extend the set of relationships between goals beyond means-ends links: + (++): one goal contributes positively (very positively) towards the fulfillment of another goal; - (--) one goal contributes negatively (very negatively) towards the fulfillment of another goal; sub: one goal subsumes another, I.e., if the first goal is fulfilled, so is the second; With these enhancements, we can build goal models which might be useful for strategic decision analysis

21. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 21 Goal Analysis OrderItem- - + + + ++ - - Collectorders Byperson Bysystem Haveupdatedinvoices With Shopping Cart SelectItem Manually AutomaticallyMatchingeffort Collectioneffort Minimalconflicts MinimalInteraction Rapidity of Order Minimaleffort By phone ByFax ++Availability …

22. From i* to Agent Concepts

23. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 23 Using These (i*) Social Concepts During early requirements (organization modeling), these concepts are used to model external stakeholders (people, organizations, existing systems), their relevant goals and inter-dependencies. one or a few actors During late requirements, the multi-agent system-to-be enters the picture as one or a few actors participating in i* models. During architectural design, the actors being modelled are all multi agent system actors.

24. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 24 Organization Information Systemsorganizational and system models to match theirOperational Environment Organization Information Systems must integrate organizational and system models to match their Operational Environment. –ERP systems organization –ERP systems: Process view of the enterprise to meet organizational goals, integrating all functions from the enterprise organization. –Knowledge management systems organization –Knowledge management systems help the enterprise gain insight from its knowledge hidden in the organization. SystemOrganizationalKM: IT System + Organizational Adjustments + Personnel Incentives –E-business systems organizational –E-business systems implement “virtual enterprises” on organizational patterns that drive their business processes. Why Organizational Architectures?

25. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 25 Classical Architectural Styles Main Program & Sub-Routines Layered Architecture (Mobile Robot) Pipe-filter

26. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 26 Multi-Agent Architectures as Social Structures Global architecture in terms of interconnected social components. 3 levels Organizational –1 Macrolevel : Organizational Styles (Organization Theory) Vertical Integration, Pyramid, Joint Venture, Structure in 5, Bidding, Hierarchical Contracting, Co-optation, Takeover Agent, COOPIS –2 Micro level : Patterns (Agent, COOPIS Community) Broker, Matchmaker, Contract-Net, Mediator, Monitor, Embassy, Wrapper, Master-Slave,... i* –3 Atomic : Social and intentional concepts – i*

27. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 27 Organization Theory Mintzberg, Scott, Galbraith, … Studies alternatives and models for (business) organizations Used to model the coordination of business stakeholders -- individuals, physical or social systems -- to achieve common (business) goals. Structure in 5, Pyramid, Takeover, Joint Venture, Cooptation, Hierarchical Contracting, Vertical Integration, Bidding, Merger, Equity Agreement, Virtual Organization, …

28. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 28 Structure in 5 Strategic and logistic components found in organizations. Operational core Operational core : basic operations -- the input, processing, output associated with running the organization. Strategic apex Strategic apex : executive, strategic decisions. Support Support : Assists the operation core for non-operational services outside the basic flow of operational procedures. Technostructure Technostructure : standardizes the behavior of other components, help the system adapt to its environment. Middle line Middle line : Actors who join the apex to the core.

29. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 29 Structure in 5 in i* and Telos TELL CLASS StructureIn5MetaClass IN Class WITH /*Class is a MetaMetaClass*/ attribute name: String part, exclusivePart, dependentPart ApexMetaClass: Class CoordinationMetaClass: Class MiddleAgencyMetaClass: Class SupportMetaClass: Class OperationalCoreMetaClass: Class END StructureIn5MetaClass In i* In Telos

30. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 30 Joint Venture in i* and Telos TELL CLASS JointVentureMetaClass IN Class WITH /*Class is a MetaMetaClass*/ attribute name: String part, exclusivePart, dependentPart JointManagementMetaClass: Class part, exclusivePart /*exclusive and independent part*/ PrincipalPartnerMetaClass: Classpart /*shared and independent part*/ SecondaryPartnerMetaClass: Class END JointVentureMetaClass In Telos

31. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 31 Cooptation and Bidding

32. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 32 Hierarchical Contracting and Vertical Integration

33. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 33 Software Quality Attributes Predictability, Security, Adaptability, Cooperativity, Competitivity, Availability, Integrity, Modularity, Aggregability

34. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 34 Example A Classical mobile robot layered architecture Information exchange not always straight-forward Often need to establish direct communication Data and control hierarchies not separated Prevent the dynamic manipulation of components

35. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 35 Mobile Robot Architecture: Structure-in-5 More distributed architecture

36. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 36 Goal Analysis: Selecting System Architecture

37. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 37 A Joint-Venture E-commerce Architecture E-business styles: on web, protocols, technologies Not on business processes, NFRs No organization of the architecture, conceptual high- level perspective From Security, Availability, Adaptability

38. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 38 Social Patterns Matchmaker Monitor

39. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 39 Example: Matchmaker Locates a provider corresponding to a consumer request for service, Then hands the consumer a handle to the chosen provider directly. Contrary to the broker who directly handles all interactions between the consumer and the provider, the negotiation for service and actual service provision are two distinct phases. Used in the horizontal contracting and joint venture styles.

40. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 40 AgentCapabilities Customer Build a request to query the matchmaker Handle a services ontology Query the matchmaker for a service  Find alternative matchmakers  Request a service to a provider  Manage possible provider failures  Monitor the provider’s ongoing processes Ask the provider to stop the requested service Provider Handle a services ontology Advertise a service to the matchmaker Withdraw the advertisement Use an agenda for managing the requests Inform the customer of the acceptance of the request service Inform the customer of a service failure Inform the customer of success of a service Matchmaker Update the local database Handle a services ontology  Use an agenda for managing the customer requests  Search the name of an agent for a service  Inform the customer of the unavailability of agents for a service

41. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 41 Social Patterns Embassy Mediator

42. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 42 Assigning Agent Roles to Actors

43. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 43 Detailed Design Agentin details Architectural Agent components defined in details in terms of inputs, outputs, control, and other relevant information. Shopping Cart UML Classes

44. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 44 Agent Interaction Protocol with AUML The Checkout Dialogue CustomerShopping Cart

45. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 45 Plan Diagram for checking out Check Out Plan

46. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 46 Partial JACK Implementation for checking out

47. Manuel Kolp, University of Toronto, Department of Computer Science © 2000-2001A Goal-Based Organizational Perspective on Multi-Agent Architectures 47 Conclusion Multi-Agents architectures described with concepts from requirements and organization modeling -> Narrows the gap requirements / architecture social and intentional structures Multi-Agent Architectures as social and intentional structures organization information systems Best suited to open, dynamic and distributed applications and organization information systems Ontology on 3 levels: –Macro: Organization Styles –Micro: Social Patterns –Atomic: i* components: goals, actors, social dependencies, …