Semester 1
Lecture 1 - 6th September 2010
Lecture 1 - 6th September 2010
- Introductory Lecture Slideshow
- Definition and goal of Artificial Intelligence.
- Simulating Intelligence - a machine's actions merely simulate intelligence, it does not understand the symbols it uses
e.g. think of Chinese Room example.
- An introduction to the sorts of problems we expect an intelligent system to solve.
- Knowledge Representation, Classical Logic, Probability, Fuzzy Logic, Efficient Search Algorithms
- Computer Conversations: Prolog, Natural Language Processing, Translation.
- Game Solving: 2-Player Strategy Games, CSPs.
Some of the terms we discussed:
Lecture 2 - 20th September 2010
Lecture 2 - 20th September 2010
- The comparisons & differences between how a computer works -vs- how the brain works.
- Understanding these comparisons and differences enables us to figure out where possible problems lie.
- How to go about defining a problem for a machine to understand.
- Approach to questions Intelligent system should answer
- Logic and Data Representation
- Type of knowledge we need to represent e.g. objects, events, etc.
- Entities of Knowledge: knowlegdge and symbolic levels
- Structure of simple English sentence
- Using Knowledge: learning, retrieval, reasoning.
- (covered in lab) Granularity of knowlege - at what level it should be represented.
- Different approaches: Relational, Inheritable, Procedural and Inferential
Some of the terms we discussed:
Lecture 3 - 27th September 2010
Lecture 3 - 27th September 2010
- Did quiz
- Started on Propositional Logic and Resolution
- Validity of an argument
Some of the terms we discussed:
Lecture 4 - 4th October 2010
Lecture 4 - 4th October 2010
- Propositional Resolution: Proof by Contradiction
- Axiomatic Logic and Proofs
- First problem sheet was handed out.
Some of the terms we discussed:
Lecture 5 - 11th October 2010
Lecture 5 - 11th October 2010
- Finished off propositional logic: Soundness, Consistency and Completeness.
- Started on Predicate Logic
- Extended rules to allow for variables and quantifiers.
- Showed that domain is important.
- Looked at semantics, interpretation/models.
- Resolution with predicates.
- 2nd problem sheet and assignment handed out.
Some of the terms we discussed:
Lecture 6 - 18th October 2010
Lecture 6 - 18th October 2010
- Finished off Grandparent resolution example
- Started looking at Logic Programming techniques.
- Substitutions and unification with some examples.
- Clausal logic.
Some of the terms we discussed:
Lecture 7 - 1st November 2010
Lecture 7 - 1st November 2010
- Types of Clauses: Definite, Goal, Horn
- Understanding logic programming proof techniques
- Bottom-up proofs and Top-down proofs
- SLD Resolution: Algorithm and Inference Rule.
- Went through Demonstrations for bottom-up, top-down and SLD Resolution (see demonstrations section below).
- Did some examples of Entire SLD Search Space: left/right/all selection functions.
Some of the terms we discussed:
Lecture 8 - 8th November 2010
Lecture 8 - 8th November 2010
- Finished off SLD Search Space example with variables.
- Prolog Syntax
- Natural Language Processing in Prolog
- Difference Lists and Parsing
- Introduced DCG Notation.
- Drawing out parse tree (also called syntax tree).
- Took example related to lab 6.
Some of the terms we discussed:
Lecture 9 - 15th November 2010
Lecture 9 - 15th November 2010
- Parse Tree Example.
- How to put together prolog code.
- Machine Translation.
Some of the terms we discussed:
Lecture 10 - 22nd November 2010
Lecture 10 - 22nd November 2010
- Short talks of students will appear here.
Semester 2Lecture 1 - 10th January 2011
Lecture 1 - 10th January 2011
- Reasoning with uncertainty.
- What role probability theory has in AI.
- Overview of probability concepts.
- Bayesian view of probability, Bayes' Law and inference. Networks.
- Types of Reasoning: Diagnostic, Causal (Predictive), Intercausal.
Some of the terms we discussed:
Lecture 2/3 - 17th/24th January 2011
Lecture 2/3 - 17th/24th January 2011
- Review of Prolog and Labs from Semester 1.
Lecture 4 - 3rd February 2011
Lecture 4 - 3rd February 2011
- Introduced Fuzzy Logic
- Differences between Fuzzy Set Theory and Classical Set Theory.
- Representation of Fuzzy Sets
- Fuzzy Set Operations: Complements, Intersection
- Fuzzy Rules
Some of the terms we discussed:
Lecture 5 - 10th February 2011
Lecture 5 - 10th February 2011
- Looked at Mamdani and Sugeno style fuzzy inference
- Took example involving calculating risk given project funding and staffing.
Some of the terms we discussed:
Lecture 6 - 14th February 2011
Lecture 6 - 14th February 2011
- Extended idea of min, max operators in Fuzzy Logic.
- Introduced t-norms (triangular norms), t-conorms.
- Started searching algorithms.
- Looked at simplified version of Nim.
- Discussed X's and O's example.
Some of the terms we discussed:
Lecture 7 - 22nd February 2011
Lecture 7 - 22nd February 2011
- Formulised searching ideas.
- Breadth-first & Depth-first Searches.
- Took alpha-beta pruning example.
- Looked at different search methods
- N-Queen's Problem
- Backtracking and Forward checking
Some of the terms we discussed:
Lecture 8 - 28th Feburary 2011
Lecture 8 - 28th Feburary 2011
- N-Queen's Problem
- Backtracking and Forward checking
- Looked at Constraint Satisfaction Problems
- Arc Consistency and Algorithm, see: csp_defns.pdf.
- Did out two examples relating to arc consistency
Some of the terms we discussed:
Lecture 9 - 14th March 2010
Lecture 9 - 14th March 2010
- Looked at Best-First Search
- Algorithm A*
- Went through some examples applying Best-First Search.
Some of the terms we discussed:
Lecture 10 - 21st March 2011
Lecture 10 - 21st March 2011
