Introduction to Artificial Intelligence
Course Descriptor
Labs
I will hold two
hands-on labs for the practical.
Notes
- Philosophy of AI
- Philosophy of AI
- Philosophy and Future of AI
- What is Intelligence?
- What is Consciousness?
- What is Life?
Concepts
- Search and Learning - state spaces,
generalisation, nearest-neighbours.
- Learning from examples - Single-layer Neural Networks,
Multi-layer Neural Networks, supervised learning, back-propagation,
Neural Networks as generalisations (of state-spaces or non-linear functions).
- Learning from rewards - Reinforcement Learning, Delayed reinforcement,
Markov worlds, exploration v. exploitation, world models.
- Artificial evolution - fitness landscapes, hill-climbing, the Genetic Algorithm,
classifier systems, Genetic Programming.
- Collective behavior - Cellular Automata, Chaos and Complexity, basins and attractors,
prediction, the Game of Life, Artificial Life.
Practical
Practical
Repeat:
Leave your write-up to my office,
or leave at the school office for me.
Library categories
- 100 - Philosophy and psychology
- 120 - Epistemology, causation, humankind
- 150 - Psychology
- 153 - Mental processes and intelligence
On Internet since 1987.
