1. M. Gams Jozef Stefan Institute
BASIC
AI METHODS
M. Gams
Jozef Stefan Institute

2. PURPOSE:
Show how AI methods work - to con-computer specialists - with a simple, understandable example

3. THE EXAMPLE:
Solution: Possibilities x 3 x 3 = 27 possibilities … no. of all particles in the universe

4. GENETIC ALGORITHMS
Population evolution: breeding, selection; competition, better adapted offsprings – only the best survive Genetic code of an individual is represented by a sequence of digits, 3 seeds: 111, 222, 321 Cross-over (breeding) (2), 212(0), 221(1), 211(0), 121(2), 112(1) () 123 Mutation (each third individual, next position, +1) 222(1), 212(0), 221(1), 221(1), 121(2), 112(1)

5. GENETIC ALGORITHMS
111, 222, (1), 212(0), 221(1), 221(1), 121(2), 112(1) (2), 311(0), 321(1), 111(1), 121(2), 111(1) (0), 321(1), 322(1), 323(2), 222(1), 221(1) 3 BEST: 121(2), 122(2), 323(2) NEXT STEP: SEVERAL SOLUTIONS 123(3)

6. RULES:
if high_fever then illness if fever > 37 then illness if (axilliar = yes) and (degree of diff = fairly) and (lung = no) and (sex = female) then breast (100%) Solution: if x1=1 and x2=2 in x3=3 then (3).

7. RULES:
Start: candidates First step: if x1=1 then (1) if x1=2 then (0) if x1=3 then (0) Next step: if x1=1 and x2=2 then (2) if x1=2 and x2=2 then (1) Next step: if x1=1 and x2=2 and x3=3 then solution (3)

8. Idea – repeat splitting the space of all possibilities
11(1)
12(2)
13(1)
121(2)
122(2)
123(3)
x1=1
2x2x3
3x2x3
1x2x3 NE DA
x2=2
x3=3
123
11x3
13x3
12x3
TREES:
Idea – repeat splitting the space of all possibilities

9. Output(neuron) = 1 if Σ wi xi > C
NEURAL NETWORKS:
Output(neuron) = 1 if Σ wi xi > C
0 otherwise
Our case: 9 connections
if w1 = 1, w5 = 1 w9 = 1, Σ wi xi = 3
x1 x2 x3

10. NEURAL NETWORKS:
  Learn weights wi examples in a sequence (1) (3) (0) (1) (0) (1) (2) (2) (1) (1) (1) (1) (1) (2) (0) (0) (0) (0) (1) (2)

11. CONCLUSION
  - DIFFERENT AI SEARCH METHODS GENETIC/EVOLUTIONARY METHODS RULE-CONSTRUCTING MACHINE LEARNING TREE-CONSTRUCTING NEURAL NETWORKS AROUND 10 ADDITIONAL METHODS SOME DETERMINISTIC, OTHER SOFT DIFFERENT METHODS APPROPRIATE FOR DIFFERENT PROBLEMS AND TASKS - EFFECTIVE, MANY TOOLS