This course will present advanced topics in Artificial Intelligence (AI). We will begin by defining the term “software agent” and discussing how software agents differ from programs in general. We will then take a look at those problems in the field of AI that tend to receive the most attention.
This course will present advanced topics in Artificial Intelligence (AI). We will begin by defining the term “software agent” and discussing how software agents differ from programs in general. We will then take a look at those problems in the field of AI that tend to receive the most attention. Different researchers approach these problems differently. In this course, we will focus on how to build and search graph data structures needed to create software agents, an approach that you will find useful for solving many problems in AI. We will also learn to “break down” larger problems into a number of more specific, manageable sub-problems.
In the latter portion of this course, we will review the study of logic and conceptualize the differences between propositional logic, first-order logic, fuzzy logic, and default logic. After learning about statistical tools commonly used in AI and about the basic symbol system used to represent knowledge, we will focus on artificial neural network and machine learning, which are essential components of computational and statistical methods, and theoretical computer science. The course will then conclude with a study of the Turing machine and a discussion of the questionable claims that human thinking is a symbol manipulation.
Upon successful completion of this course, students will be able to:
Define the term “intelligent agent,” list major problems in AI, and identify the major approaches to AI.
Translate problems into graphs and encode the procedures that search the solutions with the graph data structures.
Explain the differences between various types of logic and basic statistical tools used in AI.
List the different types of learning algorithms and explain why they are different.
List the most common methods of statistical learning and classification and explain the basic differences between them.
Describe the components of Turing machine.
Name the most important propositions in the philosophy of AI.
List the major issues pertaining to the creation of machine consciousness.
Design a reasonable software agent with java code.
