Course - Artificial Intelligence MT24
- Course Webpage
- Lecture Notes
- 1, Introduction
- 2, Problem solving and search
- 3, Problem solving and search
- 4, Informed search
- 5, Local search
- 6, Planning I
- 7, Planning II
- 8, Dealing with geometry of physical agents
- 9, Dealing with geometry of physical agents
- 10, Introduction to CSPs
- 11, Solving CSPs
- 12, Solving CSPs
- 13, Playing games
- 14, Playing games
- 15, Beyond classical search
- 16, Beyond classical search
- Other courses this term: [[Courses MT24]]U
- Related textbooks: [[AI - A Modern Approach]]N
Timetable
- Wednesday 3PM-4PM, Bill Roscoe Lecture Theatre (weeks 1-6)
- Friday 3PM-4PM, Bill Roscoe Lecture Theatre (weeks 1-8)
- Friday 2PM-3PM, Bill Roscoe Lecture Theatre (weeks 7-8)
Notes
- [[Notes - Artificial Intelligence MT24, Problem solving and search]]U
- [[Notes - Artificial Intelligence MT24, Uninformed search]]U
- [[Notes - Artificial Intelligence MT24, Informed search]]U
- [[Notes - Artificial Intelligence MT24, Local search]]U
- [[Notes - Artificial Intelligence MT24, Planning]]U
- [[Notes - Artificial Intelligence MT24, Partial order planning]]U
- [[Notes - Artificial Intelligence MT24, Planning with propositional logic]]U
- [[Notes - Artificial Intelligence MT24, Robots]]U
- [[Notes - Artificial Intelligence MT24, Constraint satisfaction problems]]U
- [[Notes - Artificial Intelligence MT24, Playing perfect information games]]U
- [[Notes - Artificial Intelligence MT24, Nondeterministic search]]U
- [[Notes - Artificial Intelligence MT24, Partially observable environments]]U
- [[Notes - Artificial Intelligence MT24, Online search]]U
Related notes
Some more notes on the course textbook are available in [[AI - A Modern Approach]]N, but the following are particularly relevant to this course:
- I: Introduction
- Chapter 01: [[AIMA - Introduction]]N
- Chapter 02: [[AIMA - Intelligent Agents]]N
- II: Problem Solving
- Chapter 03: [[AIMA - Solving Problems by Searching]]N
- Chapter 04: [[AIMA - Constraint Satisfaction Problems]]N
- Chapter 05: [[AIMA - Adversarial Search and Games]]N
- Chapter 06: [[AIMA - Search in Complex Environments]]N
- III: Knowledge, Reasoning, and Planning
- Chapter 07: [[AIMA - Logical Agents]]N
- Chapter 08: [[AIMA - First-Order Logic]]N
- Chapter 09: [[AIMA - Inference in First-Order Logic]]N
- Chapter 10: [[AIMA - Knowledge Representation]]N
- Chapter 11: [[AIMA - Automated Planning]]N
Problem Sheets
Practicals
To-do List
- Does $IDA^\star$ need a proof of optimality for admissible heuristics or does it follow immediately from the proof of optimality for ordinary $A^\star$?
- Disjoint subproblems in general?
- Proofs for completeness/optimality/time complexity/space complixty of uniformed and informed search algorithms
- Details about building partial order plans
- Understand faster implementation of the sweep algorithm
- Does the Tree CSP algorithm only work when the CSP is binary?
-
Better understanding of tree decomposition algorithm, tree decompositions in general
- There are three requirements, but is there another more basic one
- Example for alpha beta search
- Averaging over clairvoyance (13-14 playing games)
- Go over problem sheet solutions