{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "1. **Exhaustive search** - explore all combinations. This eliminates any doubt. [Ken Thompson](https://en.wikipedia.org/wiki/Ken_Thompson)\n",
    "2. **Satisficing search** - explore convenient combinations until a solution is found that is good enough. [Herbert Simon](https://en.wikipedia.org/wiki/Herbert_A._Simon)\n",
    "3. **Approximation** - If it is too hard to find a precise solution on the original problem, make a simplified model of the problem and use its solution.\n",
    "4. **Heuristics** - \"If you don't know how to solve a particular problem, use a method that solves similar problems and modify it.\" [George Polya](https://en.wikipedia.org/wiki/George_P%C3%B3lya)\n",
    "5. **Greedy Strategy** - Identify the single biggest gain, keep it & repeat the search on the remainder of the problem.\n",
    "6. **Marginal search** - Use a method to construct an initial solution, then use another method to search for marginal improvements to the initial solution.\n",
    "7. **Ensemble search** - From a pool of candidate methods, try them all and pick the best solution. \n",
    "8. **Divide and conquer** - split the problem into smaller subproblems, divide each subproblem further until solveable, then combine the partial solutions.\n",
    "9. **Novelty search** - \"don't try to solve the problem. Try instead to discover novel features and if they work, explore them further.\" [Kenneth Stanley](http://2018.alife.org/events/kenneth-o-stanley/) \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}