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The El Farol Bar Problem for next generation systems

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3.3. BUDGET ALGORITHMS 33<br />

probabities <strong>for</strong> each agent<br />

probabities <strong>for</strong> each agent<br />

probabities <strong>for</strong> each agent<br />

1.0<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

0.0<br />

0 1000 2000 3000 4000 5000<br />

time (iterations)<br />

1.0<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

0.0<br />

0<br />

1.0<br />

1000 2000<br />

time (iterations)<br />

3000 4000<br />

0.8<br />

0.6<br />

0.4<br />

0.2<br />

0.0<br />

0 1000 2000 3000 4000 5000<br />

time (iterations)<br />

attendance<br />

attendance<br />

attendance<br />

100<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0 1000 2000 3000 4000 5000<br />

time (iterations)<br />

100<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0<br />

100<br />

1000 2000<br />

time (iterations)<br />

3000 4000<br />

80<br />

60<br />

40<br />

20<br />

0<br />

0 1000 2000 3000 4000 5000<br />

time (iterations)<br />

Figure 3.6: <strong>The</strong> overall attendance and the probabilities <strong>for</strong> each of the M<br />

agents <strong>for</strong> budget (budget= 10) and modified budget (budget= 10, wait=3, 6)<br />

algorithms.

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