CS261W. AI and Information
Introduces the basics of artificial intelligence and information management.
Prerequisites: introduction to computer science (any implementation of CS103 or CS112), discrete structures (CS106 or CS115)
Syllabus:
- Fundamental issues in intelligent systems: History of artificial intelligence; philosophical questions; fundamental definitions; philosophical questions; modeling the world; the role of heuristics
- Search and constraint satisfaction: Problem spaces; brute-force search; best-first search; two-player games; constraint satisfaction
- Knowledge representation and reasoning: Review of propositional and predicate logic; resolution and theorem proving; nonmonotonic inference; probabilistic reasoning; bayes theorem
- Advanced search: Genetic algorithms; simulated annealing; local search
- Machine learning and neural networks: Definition and examples of machine learning; supervised learning; learning decision trees; learning neural networks; learning belief networks; the nearest neighbor algorithm; learning theory; the problem of overfitting; unsupervised learning; reinforcement learning
- Information models and systems: History and motivation for information systems; information storage and retrieval; information management applications; information capture and representation; analysis and indexing; search, retrieval, linking, navigation; information privacy, integrity, security, and preservation; scalability, efficiency, and effectiveness
- Database systems: History and motivation for database systems; components of database systems; DBMS functions; database architecture and data independence
- Data modeling: Data modeling; conceptual models; object-oriented model; relational data model
- Relational databases: Mapping conceptual schema to a relational schema; entity and referential integrity; relational algebra and relational calculus
- Database query languages: Overview of database languages; SQL; query optimization; QBE and 4th-generation environments; embedding non-procedural queries in a procedural language; introduction to Object Query Language
Units covered:
| IS1 | Fundamental issues in intelligent systems | 1 | core hour |
| IS2 | Search and constraint satisfaction | 5 | core hours |
| IS3 | Knowledge representation and reasoning | 4 | core hours |
| IS4 | Advanced search | 3 | hours |
| IS8 | Machine learning and neural networks | 3 | hours |
| IM1 | Information models and systems | 3 | core hours |
| IM2 | Database systems | 3 | core hours |
| IM3 | Data modeling | 4 | core hours |
| IM4 | Relational databases | 3 | hours |
| IM5 | Database query languages | 3 | hours |
| SP6 | Intellectual property | 1 | core hour (of 3) |
| | Elective topics | 7 | hours |
Notes:
[to be supplied]
Online resources for CS261W