Introduction to Agent Technology in Mobile Environment Course Introduction Vagan Terziyan Department of Mathematical Information Technology University of Jyvaskyla ; ITIN, France, February 2006

2 Contents §Practical Information §Course Introduction §Lectures and Links §Course Exercise and self-study

3 Practical Information Lectures: 10 hours Thursday: 23 February, 9:00-10:15; 10:30-12:00; 13h30-15h15; Friday: 24 February, 9:00-10:15; 10:30-12:00.  Slides available online (links from Introductory Lecture) Exercise: 6 hours Thursday: 23 February, 15:30-17:00 Friday: 24 February, 13:30-15:15; 15:30-17:00.  task will be announced during the lectures

4 Introduction: Semantic Web - new Possibilities for Agent-Driven Applications

5 Agents in Mobile Environment (sample scenario)

6 Motivation for Semantic Web

7 Semantic Web Content: New “Users” applications agents

8 Semantic Web: Resource Integration Shared ontology Web resources / services / DBs / etc. Semantic annotation

9 Semantic Web: What to Annotate ? Web resources / services / DBs / etc. Shared ontology Web users (profiles, preferences) Web access devices Web agents / applications External world resources Smart machines and devices

10 Word-Wide Correlated Activities Semantic Web Grid Computing Web Services Agentcities Agentcities is a global, collaborative effort to construct an open network of on-line systems hosting diverse agent based services. WWW is more and more used for application to application communication. The programmatic interfaces made available are referred to as Web services. The goal of the Web Services Activity is to develop a set of technologies in order to bring Web services to their full potential FIPA FIPA is a non-profit organisation aimed at producing standards for the interoperation of heterogeneous software agents. Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation Wide-area distributed computing, or "grid” technologies, provide the foundation to a number of large-scale efforts utilizing the global Internet to build distributed computing and communications infrastructures.

11 GENI – Next Generation Internet §GENI - Global Environment for Networking Investigations (proposed 25 August 2005) §The U.S. National Science Foundation (NSF) has proposed a next-generation Internet with built-in security and functionality that connects all kinds of devices, with researchers challenging the government agency to look at the Internet as a "clean slate." §The GENI Initiative envisions the creation of new networking and distributed system architectures that, for example: l Build in security and robustness; l Enable the vision of pervasive computing and bridge the gap between the physical and virtual worlds by including mobile, wireless and sensor networks; l Enable control and management of other critical infrastructures; l Include ease of operation and usability; and l Enable new classes of societal-level services and applications.

12 GUN vs. GENI GUN initiative intends to provide tools and solutions to make heterogeneous industrial resources (files, documents, services, devices, processes, systems, human experts, etc.) web-accessible, proactive and cooperative in a sense that they will be able to analyze their state independently from other systems or to order such analysis from remote experts or Web-services to be aware of own condition and to plan behavior towards effective and predictive maintenance. GUN G lobal U nderstanding e N vironment Agent Technologies is a key advantage !

13 Resource History Ontology Templates Roles Goals Behaviour rules Resource Agent Behaviour Templates Executable modules or Web Services R GB DF on a GUN Platform

14 One of Smart Resource Scenarios “Expert” “Service” Labelled data Diagnostic model Querying diagnostic results Labelled data Watching and querying diagnostic data Labelled data History data “Device” Querying data for learning Learning sample and Querying diagnostic results “Knowledge Transfer from Expert to Service” Agent plays roles: Scene 1: “patient”; Scene 2: “teacher”; Scene 3: “patient” Agent plays roles: Scene 1: “diagnostic expert”; Scene 2: “no play”; Scene 3: “no play” Agent plays roles: Scene 1: “no play”; Scene 2: “student”; Scene 3: “diagnostic expert”

15 ATME Course: Lectures

16 Semantic Web Lectures Lectures Schedule 23/02/2006 (9: :15) – Lecture 1: What is an Intelligent Agent? 23/02/2006 (10: :00) – Lecture 2: Agent Technologies 23/02/2006 (13: :15) – Lecture 3: Agent Architectures 24/02/2006 (9: :15) – Lecture 4: Mobile Personalization with Agents 24/02/2006 (10: :00) – Lecture 5: Industrial Agent-Driven Smart Resources

17 Introduction

18 Lecture 1: What is an Intelligent Agent ?

19 Lecture 2: Agent Technologies

20 Lecture 3: Agent-Based Content Management Architectures

21 Lecture 4: Mobile Personalization with Agents

22 Lecture 5: Industrial Agent-Driven Smart Resources

23 Additional Material for Self-Study

24 Agent Standards

25 Designing Software Agents with JADE

26 JADE (Java Agent DEvelopment Framework)

27 Related Course §Agent Technologies in the Semantic Web § ; §by Vadim Ermolayev; §recommended as additional reading.

28 Course Exercise

29 Alternative 1 for software engineers

30 Develop Agent(s) with JADE §Try to develop simple agent scenario based on JADE (or JADE+Eclipse) development environment; §Possible scenario: agent which sends e- mails with fixed congratulation text to the persons from the address book who have a birthday; §Any other scenario of your choice will be OK

31 Alternative 2 no software development, just a report

32 Task for the Exercise (according to A. Raja) (1) Consider the home of the future where there are software agents in a mobile environment that are helping to manage the running of a house. There will be: §(1) Personal assistant agents that will know of your preferences of temperature, humidity, light, sound, etc., and who you want to interact with; §(2) There will be agents that can measure appropriate environmental conditions with specific devices; §(3) There will be agents that effect appropriate environmental conditions with specific devices; §(4) There will be agents that control expenses for the use of appropriate devices; §(5) There will be agents that manage the telephone communications; §(6) There will be agents that manage security issues such as fire, earthquake, flood protection, etc.

33 Task for the Exercise (according to A. Raja) (2) §Assume that the agents are heterogenous (i.e. have not be generated by one designer), for example when you get a new device it will come with an agent; for instance, the heating measurement agent may not come from the same company as the air-conditioning agent. §Think about the possibility of having these agents work together. What are the capabilities of the agents, what type of cooperation needs to occur among them, are there needs for the agents to negotiate, are there situations where local objectives are at odds with global objectives such as minimizing electrical usage? What type of information needs to be exchanged among the agents?

34 Task for the Exercise (according to A. Raja) (3) §How would you organize the agents – would you have a hierarchy of agents in terms of their control responsibilities? How would you allow agents to integrate new agents into the system, for instance, when you buy a new device. §What are the specific characteristics required by a language in order that these agents can share information? If there are no dedicated resources for each agent, but rather a pool of resources that can be used by agents, what new issues does this introduce? Do agents need to reason about the intentions of other agents?

35 Task for the Exercise (according to A. Raja) (4) §In answering these and related issues that you may consider, please be concrete with specific and numerous examples/scenarios. You should first start out the effort by detailing the collection of agents that you see in the house of the future, what their responsibilities are, and their patterns of interaction with other agents. §Outcome of the exercise is report. Including figures, it should be 3-5 pages long.