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Global Domination -RISK-

Global Domination -RISK-. Table of Contents. Introduction Type Of Game Formats Game Play Artificial Intelligence Type of A.I. Variations of the A.I. Improvements to the A.I. Introduction. Type of game History of the game Platforms. Type of game. Turn based strategy game

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Global Domination -RISK-

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  1. Global Domination-RISK-

  2. Table of Contents • Introduction • Type Of Game • Formats • Game Play • Artificial Intelligence • Type of A.I. • Variations of the A.I. • Improvements to the A.I.

  3. Introduction • Type of game • History of the game • Platforms

  4. Type of game • Turn based strategy game • Multiple computer players available • Choices range 2 – 6 players • Multiple variations of the rules • Set number of troops for “turning in a book” • Increasing number of troops for “turning in a book”

  5. History • Created by Hasbro • Originally a board game • First computer version was available with Commodore 64, and IBM compatible machines • B.P. (Before Pentium) • Many different versions exist for marketability (Lord of the Rings, Star Wars, etc…)

  6. Platforms • PC • 400mhz+ for good game play • Windows ’95 or greater • Slight problems with Windows XP • Mac • Play Station 2 • Evaluation Version: PC

  7. Game Play • Initial number of troops to set on a random deal of countries • Each turn you get reinforcements based on the number of countries you control, and the continents you control • Cards are given at the end of the turn if a successful conquest took place • Cards will have a cannon, Knight, or soldier on it. • A book can be three of a kind, or one of each • Goal is to: • Overpower opponents • Defeat them from the game • Conquer the world

  8. Artificial Intelligence • Risk utilizes prediction algorithms and battle strategies • Actual algorithms were not disclosed • Popular heuristic algorithm were more than likely used within a powerful rule based system for the battle strategy • Rule Based systems often use human experts as guides

  9. Different Algorithms • Exhaustive Search • Good for simple games (Tic-Tac-Toe) • More than likely not used for Risked based on the number of combinations and decisions to take into account

  10. Improved Searches • Main goal of a prediction algorithm is to make an informed search to locate as few open states as possible based on the search diagram • Such Heuristic searches can be: • Best-First (hill climbing) • A* • Minimax

  11. Best First Search • Expand the current node • Evaluate its children • Moves onto best child for further expansion

  12. A* • If algorithm A is used with an evaluation function in which h(n) <= to the cost of the minimal path from n to the goal • Given a search function h(n) • Known starting point and goal • A* will produce the shortest path • For game design, these parameters may not be known

  13. Minimax • Assumes that the opponent or opponents use the same knowledge of the play space, and uses that knowledge to win the game • Opponents are referred to as Min and Max • Max represents player trying to win • Min is the opponent trying to minimize Max’s score

  14. Minimax cont… • Most logical course of action for any strategy game • When incorporated into a battle strategy system • Can predict to a point a player’s next move. • Improvements to the searching algorithm and other variances can create a more difficult A.I.

  15. Battle Strategies • Rule based • Situation Based • Game of this level would have an extensive system

  16. Improvements • Improving both the search algorithms and case bases • Results in different levels of A.I. • Results in a superior game with each new release

  17. This version • By allowing the user to change the way the over all game is played • Adjusts the variables for both the heuristic searches and battle strategies

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