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fix import in the example, Update results
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‎js/ai/qlearn/examples/dodgeShoot/dodgeShoot.js‎

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export { start };
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import { deepCopy } from "../node_modules/utilsac/utility.js";
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import { deepCopy } from "../../node_modules/utilsac/utility.js";
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import { randomDecide } from "../../source/randomDecide.js";
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import { createIntelligence, decide } from "../../source/qlearn.js";
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import { draw } from "./draw.js";

‎js/ai/qlearn/examples/dodgeShoot/results.txt‎

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‎js/ai/qlearn/examples/dodgeShoot/results2.txt‎

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random positive reward 2000 frames score: 135
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 2000 frames score: 476
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 2000 frames score: 470
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) positive reward 2000 frames score: 231
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 2000 frames score: 289
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 2000 frames score: 203
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) positive reward 2000 frames score: 231
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 2000 frames score: 222
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 2000 frames score: 127
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) positive reward 2000 frames score: 231
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random negative reward 2000 frames score: -119
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 2000 frames score: -18
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 2000 frames score: -23
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) negative reward 2000 frames score: -231
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 2000 frames score: -79
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 2000 frames score: -109
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) negative reward 2000 frames score: -231
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 2000 frames score: -58
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 2000 frames score: -61
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) negative reward 2000 frames score: -231
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random positive reward 20000 frames score: 1256
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 20000 frames score: 4976
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 20000 frames score: 4970
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) positive reward 20000 frames score: 2331
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 20000 frames score: 3289
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 20000 frames score: 4497
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) positive reward 20000 frames score: 2331
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 20000 frames score: 2322
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 20000 frames score: 1377
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) positive reward 20000 frames score: 2331
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random negative reward 20000 frames score: -1275
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 20000 frames score: -189
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 20000 frames score: -252
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) negative reward 20000 frames score: -2331
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 20000 frames score: -497
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 20000 frames score: -971
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) negative reward 20000 frames score: -2331
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 20000 frames score: -586
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 20000 frames score: -617
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) negative reward 20000 frames score: -2331
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random positive reward 200000 frames score: 12420
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 200000 frames score: 49976
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 200000 frames score: 49970
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) positive reward 200000 frames score: 23331
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 200000 frames score: 33289
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 200000 frames score: 49497
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) positive reward 200000 frames score: 23331
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 200000 frames score: 23322
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 200000 frames score: 13898
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) positive reward 200000 frames score: 23331
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random negative reward 200000 frames score: -12459
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 200000 frames score: -1892
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 200000 frames score: -2579
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage2) negative reward 200000 frames score: -23331
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 200000 frames score: -4868
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 200000 frames score: -9505
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage2) negative reward 200000 frames score: -23331
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 200000 frames score: -5690
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 200000 frames score: -6272
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage2) negative reward 200000 frames score: -23331
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random positive reward 2000 frames score: 123
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 2000 frames score: 463
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 2000 frames score: 465
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 2000 frames score: 420
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 2000 frames score: 214
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 2000 frames score: 233
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 2000 frames score: 129
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random negative reward 2000 frames score: -120
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 2000 frames score: -18
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 2000 frames score: -23
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 2000 frames score: -83
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 2000 frames score: -128
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 2000 frames score: -49
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 2000 frames score: -60
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random positive reward 20000 frames score: 1241
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 20000 frames score: 4963
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 20000 frames score: 4965
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 20000 frames score: 4920
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 20000 frames score: 4168
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 20000 frames score: 2333
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 20000 frames score: 1438
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random negative reward 20000 frames score: -1235
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 20000 frames score: -180
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 20000 frames score: -255
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 20000 frames score: -554
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 20000 frames score: -983
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 20000 frames score: -549
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 20000 frames score: -621
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random positive reward 200000 frames score: 12442
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qLearn(reduceStateAndActionSeeAll)(learn) positive reward 200000 frames score: 49963
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) positive reward 200000 frames score: 49965
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qLearn(reduceStateAndActionSeeAllDistance)(learn) positive reward 200000 frames score: 49920
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) positive reward 200000 frames score: 46168
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) positive reward 200000 frames score: 23333
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) positive reward 200000 frames score: 14382
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random negative reward 200000 frames score: -12370
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qLearn(reduceStateAndActionSeeAll)(learn) negative reward 200000 frames score: -1884
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qLearn(reduceStateAndActionSeeAll)(learnWithAverage) negative reward 200000 frames score: -2587
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qLearn(reduceStateAndActionSeeAllDistance)(learn) negative reward 200000 frames score: -4823
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qLearn(reduceStateAndActionSeeAllDistance)(learnWithAverage) negative reward 200000 frames score: -9479
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qLearn(reduceStateAndActionSeeNearestOnly)(learn) negative reward 200000 frames score: -5707
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qLearn(reduceStateAndActionSeeNearestOnly)(learnWithAverage) negative reward 200000 frames score: -6299

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