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| CSCI 580: Introduction to Artificial Intelligence |
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Prerequisites: Grade of C- or better in CSCI 311-Algorithm and Data Structures.
Catalog Description:
An introduction to the basic principles, techniques, and applications of Artificial Intelligence. Coverage includes knowledge representation, logic, inferencing, problem solving, search algorithms, game theory, perception, learning, planning, and agent design. Students will program with AI language tools. Additional areas may include expert systems, machine learning, natural language processing, and computer vision. Formerly CSCI 223
Course Objectives:
The primary objective of this course is to introduce the basic principles, techniques, and applications of Artificial Intelligence. Emphasis will be placed on the teaching of these fundamentals, not on providing a mastery of specific software tools or programming environments. Assigned projects promote a 'hands-on' approach for understanding, as well as a challenging avenue for exploration and creativity.
Specifically:
- Gain a historical perspective of AI and its foundations. (I)
- Become familiar with basic principles of AI toward problem solving, inferencing, perception, knowledge representation, and learning. (I)
- Investigate applications of AI techniques in intelligent agents, expert systems, artificial neural networks and other machine learning models. (I)
- Experience programming in an 'AI language' and an expert system shell. (I)
- Experiment with a machine learning model for simulation and analysis. (B)
- Discuss the potential, limitations, and implications of intelligent systems. (I)
B=Basic I=Intermediate A=Advanced
Course Outcomes:
Students will have developed the ability to:
- Accurately discuss and reflect on historical aspects/systems/limitations of AI.
- Analyze complex problems in terms of agent terminology, problem formulation, goal formulation, and PAGE descriptors.
- Evaluate solution methods based on problem specifications, domain limitations, and search criteria
- Implement informed, uninformed, and complex search algorithms, within the context of an intelligent system.
- Decipher, modify, and implement simple solutions for performing pattern matching.
- Formulate knowledge representations and domain specific rules and constraints.
- Reason about rules of inference, specifically induction, substitution, and resolution.
- Design and develop basic LISP programs and intermediate-level Expert Systems.
- Generate solutions invoking learning, using hi-level AI simulation/development tools for the automated creation of neural networks, genetic algorithms, or hybrid models.
- Perform system benchmarking, to compare performance of AI tools/applications.
- Analyze, design, and develop prototype systems or frameworks for complex (often intractable) problems.
- Reason intelligently about the philosophical issues and sociological implications for the future of AI systems and development.
- Perform basic research and critique of AI literature, while honing their own writing and communication skills focusing on scientific writing, precision, and accuracy.
Class/Laboratory Schedule:
Three hours per week in lecture/discussion, minus six hours spent together in lab activity over the course of the semester.
Accreditation Category Content:
This course embodies a significant portion of (a) Theoretical Foundations, (b) Problem Analysis, and (c) Solutions Design. |
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| Topic |
Percentage |
Hours |
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| Algorithms |
38% |
17 |
| Data Structures |
9% |
4 |
| Software Design |
33% |
15 |
| Concepts of Programming |
11% |
5 |
| Computer Organization and Architecture |
2% |
1 |
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Relationship of Course to Program Objectives:
This course supports the achievement of the following program objectives:
- All students will be able to analyze and solve computing problems, or problems in related areas, and to continually upgrade their knowledge and skills. (P)
- All students will be effective oral and written communicators and be able to function effectively as members of multi-disciplinary teams. (P)
- All students will have an appreciation for the individual, society, and human heritage and they will be aware of the impact of their work on society and the environment. (R)
- Those graduates who pursue careers as computing professionals will have the skills to use and design new and innovative systems that meet society's needs. (P)
- Those graduates who pursue advanced degrees will have the skills to succeed in graduate programs in computing and related fields. (R)
I=Introduced P=Practiced R=Reinforced |
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Management
California State University, Chico |
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Science, & Construction Management
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