Reference no: EM132551123
Unit 27 Artificial Intelligence
Code - L/615/1663
Introduction
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 behaviours - vision, speech and voice recognition, smelling sense, learning from experience to solve new problems and coping with the unknown. The science of artificial intelligence (Al) is trying to overcome these challenges by combining the study of nature, understanding from humans' intelligent behaviour and brain function, other animal's acute senses, with mathematics, statistics, logic and traditional computer science. Some of Als 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.
This unit is designed to introduce the philosophy behind artificial intelligence, the most efficient techniques of Al and various intelligent systems that help us to overcome various challenges. This unit guides the student to investigate the emerging Al technologies which could solve various real-world challenges and problems.
Topics included in this unit are the philosophical background to Al, current trends and the future of Al, ethics and issues in Al ,a range of AI applications (computer vision, speech processing and so forth), top-down approach of AI techniques, fuzzy logic, knowledge-based systems, natural language processing), bottom-up approach of Al techniques (neural networks, evolutionary computing, swarm intelligence), and emerging Al technologies (Brain Computer Interfacing, Ambient AI, Smart City, GPU Al etc).
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. Furthermore, the students can gain hands-on experience in developing intelligent systems using a programming language such as C/C++, C#, Java, Prolog, Lisp, Python, R, or a tool such as Weka, KNIME, MS AzureML, Accord.NET, AForge.NET, Neuroph, tools for NLP (NLTK, AIML), tools for swarm robotics (Microsoft robotics developer studio, Orocos, 'Player Stage Gazebo') etc.
As a result students will develop skills such as communication literacy, critical thinking, analysis, reasoning and interpretation, which are crucial for gaining employment and developing academic competence.
Learning Outcome 1: Analyse the theoretical foundation of artificial intelligence, current trends and issues to determine the effectiveness of Al technology.
Learning Outcome 2: Implement an intelligent system using a technique of the top-down approach of Al.
Learning Outcome 3: Implement an intelligent system using a technique of the bottom-up approach of Al.
Learning Outcome 4: Investigate and discuss a range of emerging Al technologies to determine future changes in industry.
Essential Content
LO1 Analyse the theoretical foundation of artificial intelligence, current trends and issues to determine the effectiveness of Al technology
Philosophical background of Al:
What is an intelligence? How does the brain work? What is artificial intelligence? The Turing test, John Searle's The Chinese Room' test, Strong Al vs. Weak Al, Top-down approach of Al vs. bottom up approach of Al.
Top-down approach of Al:
Knowledge-based system, natural language processing, fuzzy logic. Bottom up approach of Al:
Artificial neural networks, evolutionary computing, swarm intelligence. Applications of Al:
Intelligent Robot, intelligent agent, artificial life, computer vision, speech recognition, artificial nose, data mining and other smart technologies.
Issues of Al:
Practical difficulties in building brain like machine, ethics and social issues of AI, philosophical issues of Al - will computers control the human?
LO2 Implement an intelligent system using a technique of the top-down approach of Al
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. Fuzzy logic: uncertainty, fuzzy sets, fuzzy inferences, fuzzy rules.
Natural language processing: NLP techniques, parsing with generations, compositional and lexical semantics, dialogues.
LO3 Implement an intelligent system using a technique of the bottom-up approach of Al
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.
LO4 Investigate and discuss a range of emerging Al technologies to determine future changes in industry
Distributed Al; GPU Al; Ambient Al; Brain Computer Interfacing; Smart Systems, Smart Home and Smart Cities.
Attachment:- Artificial Intelligence.rar