What is Intelligence?
AI is the attempt to build computational models of cognitive processes.
AI is about generating representations and procedures that allow machines to perform tasks that would be considered intelligent if performed by a human.
A central tenet of AI is that human-like reasoning is a form of computation that may be identified, formalized and consequently automated.
Decision making problems that confront people but require expertise:
| Engineers | Design a VLSI chip to ... |
| Architects | Design a house for HM Prince of Wales |
| Medics | Is this roseola infantum or German measles? |
| Farmers | Should I spray the spuds or pick the turnips |
| Geo-engineers | Is there oil under Jesus? |
| Students | Is òxndx = ((x^(n+)1)/n+1) + const? |
| Mechanics | How should I disassemble/assemble this machinery? |
| Academics | Which wine with roast parrot, Smithers? |
Natural tasks which we seem to perform effortlessly but which turn out to be the hardest to program into a machine:
| Balancing on less than three legs |
| Avoiding lampposts |
| Recognizing your girl/boyfriend |
| Holding hands |
| Having a conversation |
A more formal list of AI problems is as follows:
| [¯] | General Problem Solvers |
| [¯] | Expert Problem Solvers |
| Symbolic maths | |
| Medical diagnosis | |
| Chemical analysis | |
| Geological surveys | |
| Engineering design | |
| [¯] | Game playing |
| [¯] | Theorem proving |
| [¯] | Perception |
| Speech | |
| Vision | |
| [¯] | Planning |
| [¯] | Natural Language Understanding |
| [¯] | Learning |
The overall plan looks like
1 Introduction to AI for engineers
Some basics and core issues
2 Problem solving and Search, impact of different representations
3 Constraints in search
4 Knowledge representation using propositional and first-order logic
5 Resolution theorem proving