Μ202. Artificial Intelligence Techniques – Agents

1. Course Identity
Course title: Artificial Intelligence Techniques – Agents
Semester: 2nd
Hours per week: 3
ECTS Units: 6

2. Aims and Objectives

The aim of this course is to give students the opportunity to understand the use Artificial Intelligence Techniques, with emphasis to Intelligent Agents and apply those techniques for problem solving in the context of an open and dynamic environment such as the web. Those problems refer to the representation and processing of information and knowledge in the web as well as to the development of web systems and services.

By completing the course students will be able to:

  • Understand the nature of problems with regards to the web and how to incorporate intelligent techniques in solving them.
  • Understand and use state of the art techniques for developing and implementing intelligent agent and multi agent systems for the web.

3. Syllabus/Content:

  • Artificial Intelligence and the web
  • Knowledge Representation and Reasoning, Logic and Logic programming, Ontologies
  • Web Searching Techniques, Search Engines, Intelligent crawling
  • Agents, Intelligent Agents, Definitions, Characteristics and principles.
  • Agent and Intelligent Agent Architectures, Rational Agents, Reactive Agents, Goal Based Agents, Hybrid Agents, Mobile Agents.
  • Multi Agent Systems
  • Agents Interaction, Communication Protocols, Synchronization, Collaboration, Negotiations.
  • Communication Languages for agents
  • Agent Developing Methodologies
  • Agent Applications in the web (i.e softbots, agents for e-commerce, shopping agents, agents and Web Services)

4. Learning & Teaching Methods

The course will be covered by weekly lectures and tutorials, complemented by e-Learning techniques. An important part of the course refers to the development of practical case studies by students, in order to develop pilot agent and multi-agent systems.

5. Assessment

Student assessment will be based on their grades of the assignments and project case studies (50%) and the grade of a final written examination (50%).

6. Software-hardware requirements

Normal PC infrastructure available at the department and Open Software systems/freeware (such as NetLogo, Java Agent Development Environment and SWI-Prolog)

7. Bibliography