1 Interoperability in Agentspace: proposal of agent interface to environment Stanisław Ambroszkiewicz IPI PAN, Warsaw, Poland Supported by ESPRIT project CRIT2 September 2000

2 FOCUS OF OUR RESARCH: Agent organizations in Cyberspace Autonomous, heterogeneous agents are supposed to form organizations! The key issues: Infrastructure Interactions: mobility, communication, services,... Semantic interoperability Understanding: negotiation, cooperation, …

3 Interoperability zagent communities A1, A2, A3, … in a world (AGENTSPACE) za community Ai consists of homogeneous agents perceiving the world, interacting and speaking their own language Li zinteroperability between heterogeneous communities: heterogeneous agents can interact and understand each other A3 A1 A2 AGENTSPACE: L1 L2 L3

4 Interoperability continued zFix agent community A1 zWhat does it mean: perceiving the world, interacting, speaking language L1, and understanding each other ??? yperfect (interaction and semantic) interoperability inside A1: xcommon interaction infrastructure is NOT necessary xexplicit meaning (ontology) of L1 is not needed ! A1 L1

5 Interoperability continued zinteroperability between heterogeneous communities: heterogeneous agents can interact and understand each other yinteraction interoperability: common interaction infrastructure; ysemantic interoperability, explicit semantics is necessary: xlanguage for ontology interchange + interpretation of O2 into O3 and vice versa xmeaning of concepts is reduced to common generic representation of the world structure A2 L2,O2 A3 L3, O3 Common interaction infrastructure OIL or generic representation of the world

6 Generic MAP architecture as Interaction Infrastructure z PEGAZ - our MAP for agents, services, and agent organizations development Java Virtual Machine Win 95/98 Internet/Intranet/WAN/LAN (TCP,UDP) LINUXSunOSMS Win NT Mobile Agent Platform - a uniform view of Cyberspace place service

7 AGENT ARCHITECTURE Environment: Agent memory, i.e. local states situations Perception Communic -ation Learning Routine execution Decision mechanism Goal Library of routines KNOW agent or service Action: communicate communicate event Interface

8 Proposal of agent interface to environment Responsible for interactions. Based on MASIF / FIPA standard. It assures interaction interoperability: migration, communication, using services, etc. The goal: means to achieve semantic interoperability Representation layer Agent interface: Communication Language Functionality layer Language layer Representation of the world (Agentspace) structure. Local event structure is the basis for the representation. Agents perceive the environment in the same way Communication Language: simple query language for homogenous agents and Meaning Interchange Language (MIL to be constructed) for heterogeneous agents

9 The idea behind zThe reason for common interface: nothing in common = no understanding, i.e. no semantic interoperability zFunctionality layer: MASIF / FIPA standard are not sufficient; still work in progress zOur proposal: yRepresentation layer as formal representation of the structure determined by the functionality level : generic MAP environment & mechanisms for acquiring knowledge from perception (already done!) yLanguage layer - MIL (Meaning Interchange Language) - work in progress

10 ENVIRONMENT of a Mobile Agent Platform place service

11 FORMAL SPECIFICATION OF GENERIC MAP ENVIRONMENT zPrimitive entities: places, agents, services, resources zPrimitive actions: migrate, use service, take (give) resource, communicate with agent (service) zEvents: each event represents an action execution - local interaction of agents, services and places involved in the execution communicate place migrate take / give use service

12 FORMAL SPECIFICATION OF GENERIC MAP ENVIRONMENT Partial order of events service...

13 AGENT MEMORY Agent’s memory: collection of variables V1, V2, …, Vk (abstraction of database) standing for concepts. concept vi = ( name, carrier, meaning ) variable vi = (identifier, type, modification way)

14 ACQUIRING KNOWLEDGE 1: FROM PERCEPTION place move where the current location is stored where names of services are stored where the info on contents is saved Update variable: at event:

15 ACQUIRING KNOWLEDGE 2: FROM COMMUNICATION Query Answer Query: what is your Vi ? Answer: my Vi=10. Agent: revision of Vi; preserve Vi, change Vi to 10 or compute new value Vi is used in the same way by the homogeneous agents !!! Homogeneous agents: Agents’ databases are of the same type, i.e., V1, V2, …, Vk (of blue agent) and V1,V2,...,Vk (of green agent), and Vi and Vi are of the same type for i=1,2,...,k

16 CONCEPT MEANING is the way the concept is used (Wittgenstein) z meaning of Vi = the way Vi is used in updating and revision updating and revision mechanisms are the same for all homogeneous agents !!! The same interfaces !!! Vi update agent revise Agent’s database Agent’s interface: Functionality layer Representation layer Language layer Vi a homogeneous agent Environment: Perception event sambrosz: meaning of concept is defined inside a community of homogeneous agents; sharing the same ontology sambrosz: meaning of concept is defined inside a community of homogeneous agents; sharing the same ontology Communication

17 Meaning Interchange Language: MIL Ontology of society A1 Concepts: v1; vi Functionality layer Representation layer Language layer Reduction of concept meaning Concept formation from / to a heterogeneous agent generic meaning of v1 (in RDFS ?) generic meaning of vi (in RDFS ?) ? ?

18 Conclusion zWhat has been done: ySpecification of the representation layer; zWhat not: yThe rest of the interface; zFuture work: yConstruction of MIL, generic rules (primitive constructors) for concept formation;

19 zMeaning of concepts (defined within a community of homogeneous agents) can be reduced to the ontology core, I.e. to the representation layer of the interface !!! zPartial semantic interoperability achieved: yIt is supposed that the functionality layer of the interface is constructed and is the standard ythe semantics of primitive resources and primitive services is supposed to be given yconstructors for complex resources and services yconstructors for complex concepts (MIL)

20 ACQUIRING KNOWLEDGE FROM COMMUNICATION continued meaning of Vi = can be reduced to the representation layer generic reduction procedure as basis for constructing MIL CASE: heterogeneous agents PROBLEM: How to convey the meaning of v1 to the agent 2? DATABASE: v1, v2,..., vk Agent 1 DATABASE: u1, u2,..., ul Agent 2 INTERFACE1 INTERFACE2 ENVIRONMENT MIL communication The same standard of INTERFACE1 and INTERFACE2

21 Perform sequence of actions a Current situation: s DECISION MECHANISM Goal: g (a desired situation) Available Routines: Learning: modify prob and cost Routine execution: Decision mechanism Dec(g,s) s g s2 f1 f2 f3 s1 f4 optimize expected cost of getting from s to g f1(s) = a (s,f1,s1, prob1, cost1) (s1,f2,s2,prob2,cost2) (s2,f3,g, prob3,cost3) (s,f4, g, prob4,cost4) fi - knowledge-based protocols si - situations

22 DECISION MECHANISM Perform sequence of actions a’ New current situation: s1 Goal: g (a desired situation) Available Routines: (s,f1,s1, prob1, cost1) (s1,f2,s2,prob2,cost2) (s2,f3,g, prob3,cost3) (s,f4, g, prob4,cost4) fi - knowledge-based protocols si - situations Routine execution: Decision mechanism Dec(g,s) s g s2 f1 f2 f3 s1 f2(s1) = a’ Learning: modify prob1 and cost1 of f1

23 SEMANTIC INTEROPERABILITY: agents can identify, communicate and understand each other to understand each other they must agree on the meaning of concepts they use! zKEY ISSUE: meaning, semantics (ontology) represented in a machine-readable way zNatural language: Can we represent the meaning of concepts (we use) explicitly, i.e. in a machine- readable way? A fundamental problem !!! zKant, Husserl, Wittgenstein, …

24 Formal approaches to semantics and semantic interoperability zTarskian semantics: semantics of a theory is given by interpretation in a model. The model is another theory !!! zOntolingua: Gruber, Guarino et al.: meaning of concept is constrained by logical axioms. z OKBC - Open Knowledge Base Connectivity, exchange standard for ontologies chosen by FIPA z XML and RDF web standards for information exchange zOIL - Ontology Interchange Language, a European project zDAML project - DARPA Agent Markup Language: a semantic language that ties the information on page to machine-readable semantics

25 OUR CONTRIBUTION in progress: basic: technology: Pegaz Formal specification of generic MAP environment Agent & service architecture An approach to semantic interoperability Development of MAP environment: information services and agent organizations yet another experimental Mobile Agent Platform Related work: ??? Reason: all MAPs create similar environment dMARS, Interrrap, Remote Agent, … DAML, FIPA, OIL, … FIPA, CLIMATE, … Related work:

26 ACQUIRING KNOWLEDGE FROM COMMUNICATION continued zAgents with different database types and different mechanisms for acquiring knowledge from perception and communication z Meaningful knowledge exchange is possible if the agents’ interface (basic functionality layer and representation layer) are built according to the same standard! zWhat is needed: common language (MIL) to interchange concept meaning, i.e. rules how the concept is used and related to common and already defined concepts Case of heterogeneous agents: