M202. Intelligent Technologies – Agents

1. Course Information:
Course Title: Intelligent Technologies – Agents
Semester: 2nd
Hours per Week: 3
ECTS Credits: 6

2. Learning Objectives

The course aims to provide students with the ability to understand the use of Artificial Intelligence techniques, specifically Intelligent Agents, in solving problems in an open and dynamic environment such as the World Wide Web. These problems involve the representation and processing of information and knowledge on the internet, as well as the design of systems and services based on the World Wide Web.

Upon completion of the course, students will:

  • Understand the nature of problems related to the World Wide Web, characterized by the vast amount of information and the multitude of services provided, and how they are addressed using Artificial Intelligence.
  • Comprehend modern design and implementation techniques for Intelligent Agents and multi-agent systems.
  • Be able to develop systems based on Intelligent Agents/multi-agent systems.

3. Course Subject:
The topics covered in the course include:

  • Artificial Intelligence and the Internet.
  • Logic, Logic Programming, Knowledge Representation and Reasoning, Ontologies.
  • Information and Knowledge Search Techniques (Web Searching Techniques, Search Engines, Intelligent Crawling).
  • Agents, Intelligent Agents, Definitions, Characteristics.
  • Agent Architectures, Intelligent Agent Architectures, Deliberative Agents, Reactive Agents, Intentional Agents, Hybrid Agents, Mobile Agents.
  • Multi-Agent Systems (or Multi-Agent Systems).
  • Agent Interaction, Protocols, Coordination, Collaboration, Negotiations.
  • Agent Development Methodologies.
  • Agent Communication Languages.
  • Applications of Agents and the Internet (e.g., softbots, agents for e-commerce, shopping agents, agents and Web Services).

4. Teaching Method:
Student education combines lectures, discussions, presentations, and practical work.

A significant part of the teaching involves case studies that students will study based on specific literature and present in groups to share the knowledge they have acquired. In addition to the literature study, students will also implement a small-scale intelligent agent (individual work) or a multi-agent system (group work) using specialized software.

5. Student Evaluation Method:
Student evaluation is based on the final written examination, the assignments they will deliver and present during the course, as well as the development of an agent system.

6. Equipment – Software Requirements:
The equipment required for student training in a laboratory environment is provided by the computer science department, and the tools used mainly belong to the category of free and/or open-source software.

7. Suggested Bibliography

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