NN + GA | JavaScript Programming Project | OrangeApple Learning Platform

{"id":26101,"student_id":10,"content":"setBackdrop('bg.png');\nlet SIZE = 20;\nlet SPEED = 3;\nlet GRAVITY = 0.25;\nlet pipe1 = createSprite('pipe.png');\npipe1.direction = 90;\nlet pipe2 = createSprite('pipe.png');\npipe2.direction = -90;\nlet pipe3 = createSprite('pipe.png');\npipe3.direction = 90;\nlet pipe4 = createSprite('pipe.png');\npipe4.direction = -90;\nlet pipe5 = createSprite('pipe.png');\npipe5.direction = 90;\nlet pipe6 = createSprite('pipe.png');\npipe6.direction = -90;\n\nlet pairA = { x: 213 * 1 + 150, y: Math.random() * 240 + 90 };\nlet pairB = { x: 213 * 2 + 150, y: Math.random() * 240 + 90 };\nlet pairC = { x: 213 * 3 + 150, y: Math.random() * 240 + 90 };\nlet pairs = [pairA, pairB, pairC];\n\nlet birds = [];\nfor (let i = 0; i \u003c SIZE; i++) {\n    let bird = createSprite('bird.png');\n    bird.vy = 0;\n    bird.x = 100;\n    bird.jump = () =\u003e { bird.vy = -6; };\n    birds.push(bird);\n}\n\nlet count = 1;\nlet best = 0;\nlet population = [];\nfor (let i = 0; i \u003c SIZE; i++) {\n    population.push(randomDNA());\n}\n\nforever(() =\u003e {\n    pipe1.moveTo(pairA);\n    pipe1.y -= 255;\n    pipe2.moveTo(pairA);\n    pipe2.y += 255;\n    pipe3.moveTo(pairB);\n    pipe3.y -= 255;\n    pipe4.moveTo(pairB);\n    pipe4.y += 255;\n    pipe5.moveTo(pairC);\n    pipe5.y -= 255;\n    pipe6.moveTo(pairC);\n    pipe6.y += 255;\n\n    birds.forEach((b) =\u003e {\n        b.vy += GRAVITY;\n        b.y += b.vy;\n        if (b.touched([pipe1, pipe2, pipe3, pipe4, pipe5, pipe6]) || b.y \u003c -50 || b.y \u003e 530) {\n            b.hidden = true;\n        }\n    });\n\n    pairs.forEach((p) =\u003e {\n        p.x -= SPEED;\n        if (p.x \u003c 0) {\n            p.x += 640;\n            p.y = Math.random() * 240 + 90;\n        }\n    });\n\n    let alive = false;\n    let target = getPipes();\n    for (let i = 0; i \u003c SIZE; i++) {\n        let b = birds[i];\n        if (b.hidden == false) {\n            let x = Math.floor((b.x - target.x) / 15);\n            let y = Math.floor((b.y - target.y) / 15);\n            let outputs = NN([x, y], population[i]);\n            if (outputs \u003e 0) b.jump();\n            population[i].fitness++;\n            alive = true;\n        }\n    };\n    if (!alive) {\n        nextGeneration();\n        resetAll();\n        count++;\n    }\n\n    for (let i = 0; i \u003c SIZE; i++) {\n        print(population[i].fitness, 10, 10 + 20 * i);\n    }\n    print('generation:' + count, 10, 420);\n    print('best:' + best, 10, 440);\n});\n\nfunction resetAll() {\n    pairA.x = 213 * 1 + 150;\n    pairA.y = Math.random() * 240 + 90;\n    pairB.x = 213 * 2 + 150;\n    pairB.y = Math.random() * 240 + 90;\n    pairC.x = 213 * 3 + 150;\n    pairC.y = Math.random() * 240 + 90;\n    birds.forEach((b) =\u003e {\n        b.y = 240;\n        b.vy = 0;\n        b.hidden = false;\n    });\n}\n\nfunction getPipes() {\n    return pairs.filter(p =\u003e p.x \u003e= 100).sort((a, b) =\u003e a.x - b.x)[0];\n}\n\nfunction sigmoid(x) {\n    return (Math.exp(x) - Math.exp(-x)) / (Math.exp(x) + Math.exp(-x));\n}\n\n// input*2 hidden*6 output*1\nfunction NN(inputs, weights) {\n    let w = weights;\n    let i = inputs;\n    let a = i[0] * w[0] + i[1] * w[1];\n    let b = i[0] * w[2] + i[1] * w[3];\n    let c = i[0] * w[4] + i[1] * w[5];\n    let d = i[0] * w[6] + i[1] * w[7];\n    let e = i[0] * w[8] + i[1] * w[9];\n    let f = i[0] * w[10] + i[1] * w[11];\n    a = sigmoid(a);\n    b = sigmoid(b);\n    c = sigmoid(c);\n    d = sigmoid(d);\n    e = sigmoid(e);\n    f = sigmoid(f);\n    let g = a * w[12] + b * w[13] + c * w[14] + d * w[15] + e * w[16] + f * w[17];\n    return sigmoid(g);\n}\n\nfunction randomDNA() {\n    let dna = [];\n    dna.fitness = 0;\n    for (let i = 0; i \u003c 18; i++) dna.push(Math.random() * 0.2 - 0.1);\n    return dna;\n}\n\nfunction nextGeneration() {\n    let newPops = [randomDNA()];\n    population.sort((a, b) =\u003e a.fitness - b.fitness);\n    best = population[SIZE -1].fitness \u003e best ? population[SIZE -1].fitness : best;\n\n    for (let i = 0; i \u003c SIZE - 4; i++) {\n        let a = Math.floor(Math.sqrt(Math.random() * SIZE*SIZE));\n        let b = Math.floor(Math.sqrt(Math.random() * SIZE*SIZE));\n        let newDNA = crossover(population[a], population[b]);\n        newPops.push(newDNA);\n    }\n    newPops = newPops.concat(population.slice(SIZE - 3));\n    population = newPops;\n    population.forEach(b =\u003e b.fitness = 0);\n}\n\nfunction crossover(a, b) {\n    let dna = [];\n    for (let i = 0; i \u003c a.length; i++) {\n        dna[i] = Math.random() \u003e 0.5 ? a[i] : b[i];\n        if (Math.random() \u003c 0.02) dna[i] = Math.random() * 0.2 - 0.1; // mutation\n    }\n    return dna;\n}","created_at":"2018-04-11T20:46:22.051+08:00","updated_at":"2022-11-03T18:31:16.286+08:00","name":"NN + GA","language":"javascript","screenshot":{"url":"/uploads/project/screenshot/26101/2543a0dd3698025ca39e8a6173f79271.jpg"},"parent_id":24426,"plugin":"","description":null,"note":null,"status":"public","like_student_ids":[],"is_featured":false,"views":505,"hashid":"rdvs4wvq","is_content_changed":false,"review_status":"unsubmitted","submitted_at":null,"reviewed_at":null,"advise":null,"is_deleted":false}