The Semantic Web Week 18: Part 4 Introduction to Web Services and Intelligent Web Agents Module Website: Practical this week:

Recap - Acquiring content for the semantic web needs tool support. - Some tools exist (eg Protégé) to acquire knowledge in SW form ie OWL ontologies - There are methods / platforms to acquire knowledge accurately and validate it to a high standard (eg CPS) - BUT the semantic web needs populating with content – how can this be done given people in general don’t understand description logic / FOL ???????

Content Acquisition - There are two types of content – - A. NEW knowledge - B. OLD information in existing, structured formats - We concentrated on A – most content initially at least will be through B - we will return to this later…

Intelligent Agents - Overview Basic Intelligent (Web) Agents are - Programs capable of flexible, autonomous behaviour in dynamic, unpredictable environments SO they should be able to - generate plans to solve goals, - execute plans, - observe, sense and gather information, - communicate, - negotiate and - co-operate with other agents. - adapt and learn – ie improve their behaviour IA make decisions when achieving goals in DYNAMIC and SOCIAL environments

Types of IA There are many dimensions n Planning Agents vs Reactive Agents n MOBILE vs Static Agents n INFORMATION Agents

WEB SERVICES.. can be considered as n “agents” as they provide services to other agents (they are not necessarily “intelligent” agents” though) n “actions” as they have “preconditions” and “effects”

CURRENT WEB SERVICES n The main web (internet) service is.. !! Examples of types of “information” agents – their effect is to increase our knowledge: n Weather forecasts n Travel Timetables, Journey Planners n Search Engines n Horoscope (!) Other agents exist that have tangible effects eg n Online Product Sales n Reservations / Bookings Exercise: map these to Agent capabilities …

Example - Mobile Virtual Agent A B D E Virtual Bank Service Booking Service MV Agent Action Book-theatre(T) Pre: seat-price(T,X)&resource(Y)&Y > X & atbooking-service(T) & Effects: ¬resoiurce(Y)&resource(Y-X)&have_ticket(T)

Semantic Web Services n Requirement: A computer-interpretable declarative description of the Service – ie its syntax, effect and other information n Agents need to be able to find (“discover”) the relevant web services that may satisfy their goals – with published costs/resources required to use the service n Agents need to be able to understand the Service protocol so that they can execute the service n Agents need to be able to reason with the published capabilities of a service to

OWL-S – “upper level ontology” OWL-S is a language for describing web services. It is built from DAML-S and is written in OWL. There are 3 parts to a web service specification: ServiceProfile ServiceModel ServiceGrounding Service presents describedby supports

OWL-S n Service Profile u What it does, what it offers u Who is offering it u What it requires of the client (eg business contact information, payment), and what effect it makes. u What service category The information here should be sufficient for an agent to ‘discover’ the service this is like the “yellow pages” entry

OWL-S n Service Model u How does it work? This contains a model of the PROCESS of the Service – and a concrete definition of F Inputs F Outputs F Preconditions F Effects Example: we could get a “service” to book our theatre seat for us… n Service Book-theatre(T) n Preconditions: seat-price(T,X)&resource(Y)&Y > X & atbooking-service(T) & n Effects: ¬resoiurce(Y)&resource(Y-X)&have_ticket(T)

OWL-S n Service Grounding u How is it used? Maps the service (process) model description and its parameters to communication- level protocols and message descriptions in the WSDL

Exercises 1. Catch up with any practical exercises you have missed this term. 2. Complete the mobile agent example with actions for getting resource (money) and logging Into a network. (Use your imagination). You could add some information adding actions! Finally write a plan using the actions you have decided. 3. Look at some web services and try to capture there behaviour using pre- and post conditions Eg Look at the National Rail journey planner. put the INPUTS into precondition logic write the OUTPUTS as logical effects 4. Internet Info: Look at and for a website on agents. What are agent cities? Look at for a website on semantic web serviceswww.daml.org/services 5. To dwell on: What is the difference between an (Intelligent) Agent and - A program or (Unix) process - An operating system