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Teaching Pure LP with Prolog and a Fair Search Rule
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Intro
The vision is easy to convey at first
The vision is easy to convey at first
But eventually non-termination rears its ugly head
But eventually non-termination rears its ugly head
Key point: it is a bit early to face non-termination!
Tabling to the (partial) rescue
Tabling to the (partial) rescue
Tabling to the (partial) rescue
Dealing with terms of unbounded size
Dealing with terms of unbounded size
Fairness to the (partial) rescue
Fairness to the (partial) rescue
Other benefits of the fair search rules
Other benefits of the fair search rules
Other benefits of the fair search rules
Other benefits of the fair search rules
Other benefits of the fair search rules
Fair search rules are great, but they cannot do the impossible
Characterization of the search tree
Depth-first search
Fair search rules: breadth-first, iterative deepening, etc.
Efficiency: depth-first vs. breadth-first vs. iterative deepening
From specifications to efficient programs
From specifications to efficient programs
Some comments on the use Peano arithmetic
Final remarks
Polynomials
Derivative (and Integrals!)
Recursive Programming: Automata (Graphs)
Recursive Programming: Automata (Graphs) (Contd.)
Recursive Programming: Towers of Hanoi
Recursive Programming: Towers of Hanoi (Contd.)
Recursive Programming: Towers of Hanoi (Contd.)
Functional Syntax
Functional Syntax
Functional Syntax
Some considerations on system types for teaching
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