tansey

        /// <summary>
        /// Saves all phenotypic progress back to the genomes.
        /// </summary>
        private void PerformLamarkianEvolution(IList<TGenome> genomeList, Func<IAgent, FastCyclicNetwork> networkSelector)
        {
            for (int i = 0; i < _agents.Length; i++)
            {
                var agent = _agents[i];

                // Get the network for this teacher

tansey

        public static double SampleGaussian(Random random, double mean, double stddev)
        {
            // The method requires sampling from a uniform random of (0,1]
            // but Random.NextDouble() returns a sample of [0,1).
            double x1 = 1 - random.NextDouble();
            double x2 = 1 - random.NextDouble();

            double y1 = Math.Sqrt(-2.0 * Math.Log(x1)) * Math.Cos(2.0 * Math.PI * x2);
            return y1 * stddev + mean;
        }

tansey

97=proba1[32]
51=proba2[32*256+35]
44=proba2[32*256+38]
51=proba2[32*256+39]
40=proba2[32*256+48]
35=proba2[32*256+49]
37=proba2[32*256+50]
51=proba2[32*256+51]
44=proba2[32*256+52]
44=proba2[32*256+53]

tansey

        /// <summary>
        /// Fits a line to a collection of (x,y) points.
        /// </summary>
        /// <param name="xVals">The x-axis values.</param>
        /// <param name="yVals">The y-axis values.</param>
        /// <param name="inclusiveStart">The inclusive inclusiveStart index.</param>
        /// <param name="exclusiveEnd">The exclusive exclusiveEnd index.</param>
        /// <param name="rsquared">The r^2 value of the line.</param>
        /// <param name="yintercept">The y-intercept value of the line (i.e. y = ax + b, yintercept is b).</param>
        /// <param name="slope">The slop of the line (i.e. y = ax + b, slope is a).</param>