One of the dreams of the computing sector is to build an intelligent digital assistant that could serve people according to peoples’ nature. Building this type of intelligent machine is a big challenge to computer scientists. An intelligent machine must have at least the following behaviors – vision, speech and voice recognition, smelling sense, learning from experience to solve new problems and coping with the unknown. The science of artificial intelligence (AI) is trying to overcome these challenges by combining the study of nature, understanding from humans’ intelligent behavior and brain function, other animal’s acute senses, with mathematics, statistics, logic and traditional computer science. Some of AIs achievements include the NASA’s Mars Rover, Google’s Self-Driving Cars, IBM’s Watson, Microsoft’s Xbox 360 (the first gaming device to track human body movement) and much more.
Who Should Attend?
Learners who want to develop skills such as communication literacy, critical thinking, analysis, reasoning and interpretation, which are crucial for gaining employment and developing academic competence can attend this course.
Course benefits:
On successful completion of this unit students will be able to understand the fundamental concepts in artificial intelligence from a theoretical, practical and cognitive point of view, and also gain innovative thought processes to build intelligent systems for future needs.
Contents
1. Analyze the theoretical foundation of artificial intelligence, current trends and issues to determine the effectiveness of AI technology.
- Philosophical background of AI: What is an intelligence? How does the brain work? What is artificial intelligence? The Turing test, John Searle’s ‘The Chinese Room’ test, Strong AI vs. Weak AI, Top-down approach of AI vs. bottom up approach of AI.
- Top-down approach of AI: Knowledge-based system, natural language processing, fuzzy logic.
- Bottom up approach of AI: Artificial neural networks, evolutionary computing, swarm intelligence.
- Applications of AI: Intelligent Robot, intelligent agent, artificial life, computer vision, speech recognition, artificial nose, data mining and other smart technologies.
- Issues of AI: Practical difficulties in building brain like machine, ethics and social issues of AI, philosophical issues of AI – will computers control the human?
2. Implement an intelligent system using a technique of the top-down approach of AI
- Choose and develop skill on a development tool or programming language which support top-down approach:
- Introduction to the language or tool; a quick tour of the language or tool; investigate and develop skill on functions, classes, libraries and/or packages which support the top-down approach.
- Choose a technique from the list below, then investigate and demonstrate the technique using the programming language or a tool: Knowledge based system: data representation, semantic net, rule-based system.
3. Implement an intelligent system using a technique of the bottom-up approach of AI
- Choose and develop skill on a development tool or programming language which support bottom-up approach:
- Introduction to the language or tool; a quick tour of the language or tool; investigate and develop skill on functions, classes, libraries and/or packages which support the bottom-up approach.
- Choose a technique from the list below then investigate and demonstrate the technique using the programming language or a tool: Artificial neural network: supervised learning algorithms, single perceptron, MLP & backpropagation learning algorithms.
- Evolutionary computing: problem model, fitness evaluation, selection method, crossover operator, evolution scheme, observation. Swarm intelligence: swarm intelligent approaches, swarm robotics, team size and composition, team configurability, communication pattern and range.
4. Investigate and discuss a range of emerging AI technologies to determine future changes in industry
Distributed AI; GPU AI; Ambient AI; Brain Computer Interfacing; Smart Systems, Smart Home and Smart Cities.
