Figure 2: Genetic algorithms and randomness

Notes: Nash equilibrium: prediction with selfish, perfectly rational agents; Human subjects: average of 4
experimental sessions; Genetic algorithm agents: selfish, boundedly rational agents (T=64,τ=32, average over 100
simulated runs, v.5.0); Zero-intelligence agents: random draws from a uniform distribution (average over 100
simulated runs v.5.6); xi ~U[0,θ] with xi iid, θ=50; Noisy Nash agents: are ZI with probability p and are best
responders to other Noisy Nash agents with probability (1-p).
More intriguing information
1. TOWARDS THE ZERO ACCIDENT GOAL: ASSISTING THE FIRST OFFICER MONITOR AND CHALLENGE CAPTAIN ERRORS2. AN IMPROVED 2D OPTICAL FLOW SENSOR FOR MOTION SEGMENTATION
3. The name is absent
4. National curriculum assessment: how to make it better
5. Skills, Partnerships and Tenancy in Sri Lankan Rice Farms
6. Quelles politiques de développement durable au Mali et à Madagascar ?
7. Large-N and Large-T Properties of Panel Data Estimators and the Hausman Test
8. LAND-USE EVALUATION OF KOCAELI UNIVERSITY MAIN CAMPUS AREA
9. Happiness in Eastern Europe
10. Experimental Evidence of Risk Aversion in Consumer Markets: The Case of Beef Tenderness