Section 1 : Introduction to artificial intelligence
Commentary
Section Goals
- To define the scope, sources, and characteristics of AI.
- To obtain the necessary background for advanced search, as well as the overall agent-oriented methodology of AI.
Section Notes
- This section is optional. Those who have taken an undergraduate AI course or have general AI knowledge can skip this section.
Learning Objectives
Learning Objective 1
- Define the role and scope of artificial intelligence.
- Describe some key historical events in the development of AI.
- Name the state-of-the-art techniques and applications of AI.
- Analyse the approaches behind some successful AI applications, such as games (e.g., IBM's Deep Blue), English grammar checking, and hand-writing recognition.
Objective Readings
Reading topics:
Introduction to AI, subfields of AI, the state-of-the-art of AI (see Chapter 1 of AIMA3ed)
Objective Questions
Discuss the following questions with your peers in the course discussion forum.
- What are the four main approaches to AI?
- What are the main research challenges of AI?
- What main approach to AI is adopted by the text? Why?
- What makes AI a separate branch of computer science?
- What degree of "intelligence" do you think or believe AI can achieve within the next twenty years?
- What makes AI methods different from other non-AI computer techniques, such as database, compiler design, and parallel computing?
Objective Activities
- Introduce yourself in the course's discussion forum (online conference).
- Join the online conference by posting your questions and answers to the course's online discussion forum.
- Complete Exercise 1.8 of AIMA3ed.
- Complete Exercise 1.14 of AIMA3ed.
Learning Objective 2
- Define the key concepts relating to agent, rationality, percept, omniscience, and autonomy.
- Define the PEAS description of task environments.
- Analyse the properties of a given task environment of an AI problem.
- Describe different agent structures, and analyse the differences between them.
Objective Readings
Required Readings
Reading topics:
- Intelligent Agents (see Chapter 2 of AIMA3ed)
Supplemental Readings
Objective Questions
- What are the main concerns in designing an agent structure?
- What are the main functions of model-based and utility-based agents?
- How can learning improve the performance and behaviour of an agent?
- What kind of task environment could be regarded as the most difficult?
- What is the difference between rationality and omniscience?
Objective Activities
- Design a general pseudo-code for model-based and utility-based agents.
- Explore agent program code from the textbook's website, including:
- Table-Driven-Agent
- Simple-Reflex-Agent
- Model-Based-Reflex-Agent
- Complete Exercise 2.2 of AIMA3ed.
- Complete Exercise 2.4 of AIMA3ed.
Discussion Questions
- Are there other aspects of intelligent agents that are popular in the AI community, other than rationality?
- What are the new innovations of intelligent agents?
- What are multi-agent systems?
- What is the relationship between distributed AI and multi-agent systems?
Relevant Conferences/Publications
- The International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS).
- Autonomous Agents and Multi-Agent Systems. Springer US. ISSN: 1387-2532. The official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems.
Learning Objective 3
- Formulate problems based on state, actions, path, and goal test to make them suitable for search.
- Explain the main search algorithms, such as tree search, graph search, depth-limited search, iterative deepening search, and bidirectional search.
- Describe the partial information issues in search, such as sensorless problems, contingency problems, and exploration problems
Objective Readings
Reading topics:
- Solving Problems by Searching (see Chapter 3.1 - 3.4 of AIMA3ed and Chapter 4.3 - 4.4 AIMA3ed)
Objective Questions
- What example problems are the most widely-used in search?
- Does iterative deepening depth-first search waste too much time in repeatedly exploring the visited nodes?
- What is the contingency problem? How are contingency problems handled?
Objective Activities
- Explore the following sample search programs from the textbook's website.
- Tree-Search
- Depth-Limited-Search
- Iterative-Deepening-Search
- Depth-Limited-Search
- Graph-Search
- Complete Exercise 3.9 of AIMA3ed.
