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title: IE502014 Artificial Intelligence - Overview
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The following plan is tentative, based on last year's plan.
There will be changes, but the rough outline will remain.
| Session | Topic | Reading | Keywords |
| :- | :- | :- | :- |
| 1 | [Introduction]() | R&N Ch. 1 | What is intelligence? Is AI possible? |
| 2 | [Rational Agents]() | R&N Ch. 2 | Instrumental reason, practical reason, etc. |
| 3 | [Search]() | | Search and Problem Solving|
| - | [AI Ethics]() | | Immplementation of ethical constraints |
| 14 | [Review]() | | Return to Session 1. In what sense is AI possible? |
| Session | Topic | Session Date | Reading | Keywords |
| :- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Introduction]() | 11 January 2024 | R&N Ch. 1 | What is intelligence? Is AI possible? |
| 2 | [Rational Agents]() | 18 Janary 2024 | R&N Ch. 2 | Instrumental reason, practical reason, etc. |
| 3 | [Search]() | 25 Janary 2024 | R&N Ch. 3.1-3.4 | Search and Problem Solving|
| 4 | [Heuristic Search]() | 1 February 2024 | R&N Ch. 3.5-3.7 | Heuristic Search |
| 5 | [Complex Environments]() | 8 February 2024 | R&N Ch. 4 | Local Search, Partional Information etc. |
| 6 | [Adversarial Search]() | 15 February 2024 | R&N Ch. 6 | Game Theory |
| - | Midterm | 19-24 February | own work |
| 7 | [Optimisation and GA]() | | H&H Chapter 1-2 | Genetic Algoritms|
| 8 | [Machine Learning and Statistics](ML)| | R&N Chapter 19 | |
| 9 | Markov Decision Processes [MDP]()| | R&N Chapter 16 | |
| 10 | ??? |
| (8/2023) | [Continuous GA]()| | H&H Chapter 3-4 | Genetic Algoritms|
| (9/2023) | [Game Theory]()| | | Game Theory, Simulation, Genetic Algorithm |
| - | Easter | 25 March - 1 April | holiday |
| 11 | ??? |
| 12 | [Reinforcement Learning]()| | R&N Chapter 23 | |
| 13 | [Deep Q-Learning]() for Reinforcement Learning | | R&N Chapter 16/23 | |
| 14 | [AI Ethics]()| 25 April 2024| | Implementation of ethical constraints |
Considering
+ Limits of AI - a review of ChatGPT and github copilot
+ R&N Chapter 7: Logical Agents
+ R&N Chapter 12: Acting under Uncertainty
# Key topics
1. Ethics.
1. What is intelligence?
- what is artificial intelligence?
- is artificial intelligence at all possible?
2. Concerns about AI
3. Machine Morality
2. Intelligence Agents
- State Machines and Graph Algorithms
- Markov Decision Processes and Reinforcement Learning
3. Optimisation and Evolutionary Algorithms
*Note* There are other modules on machine learning, so this
remains out of scope.
