Backgammon Group 1: - Remco Bras - Tim Beyer - Maurice Hermans - Esther Verhoef - Thomas Acker Introduction to backgammon Demonstration Game complexity Different AI algorithms Future plans Overview Two players Pieces are moved according to the roll of dice One player moves clockwise, other counterclockwise Pieces kicked off will be placed on the baulk Scores when reached Home Board Introduction to backgammon Lets demonstrate! Demonstration Game Complexity Neural Network The state of the board as input layer The evaluation function as hidden layer The best move as output layer AI Algorithms Reinforcement Learning (RL) Learning by playing matches against itself Temporal Difference Learning (TDL) Changes after every time step Temporal Changes through differences Difference Learning of a evaluation (value) function Learning AI Algorithms Pubeval A benchmark player by Gerry Tesauro Fixed weights Fixed strategy Used very often to compare different approaches Used for illustrating training effects AI Algorithms Implement Neural networks Vary training sessions Future Plans Week1Week2Week3Week4Week5Week6Week7 Research Implement AI Testing and debugging Improve AI Working on presentation Gannt-Chart