1. Love before Sex wan ahmad tajuddin wan abdullah
physics department, universiti malaya
50603 kuala lumpur
PERFIK : October 2004

2. Complex Systems
Adaptive ~ optimization
Exploring landscape for minimum/maximum
Landscape –
complex, changing

3. Timescale
Optimization process
fraction of single generation
memory
single generation
learning
several generations
culture
many generations
evolution

4. Evolutionary (/genetic) algorithm
Initial population
mutation
crossover
selection
new population

5. meta-evolution
Asexual/bisexual
Mating strategies ◄◄◄
...

6. self-evolution No. of sexes [PERFIK 1994]
Mating frequency, lifespans [PERFIK 1996]
Heterogeneity
Mating preferences ◄◄◄
...

7. model Fixed population size One mate per generation
Fixed lifetime (# generations)
“Physical” genes + “love” genes
Fitness: sum of first, second, … order (conjunctive) terms, randomly weighted
Choose best of a fixed no. of random suitors
Crossover: pick either parents’ genes randomly per gene

8. parameters #define NPOP 16 /** max pop size (at least NPOPS+RMATE) **/
#define NPOPS /** surviving pop size **/
#define NGEN /** total no. genes (=NGENF*(NORD+1)) **/
#define NGENF /** no. physical genes (=Nc1+2*Nc2+3*Nc3) **/
#define NORD /** order of love **/
#define NGENR /** no. generations **/
#define Nc /** first order genomes **/
#define Nc /** Second order genomes **/
#define Nc /** Third order genomes **/
#define RMUT /** Mutation rate **/
#define TMATE /** Mate choosing tries (>0) **/
#define LSPAN /** Lifespan (# generations) (>0) **/
#define RMATE /** Matings per genr (=NPOPS*0.5 if all, 0 if no sex) **/

16. conclusions Sex helps Indication that mate selection helps
Only to 1st order
Love after sex?
►►►higher statistics; analysis