Merge branch 'Dev' of ssh://gitlab.insa-rennes.fr:16022/Samuel.Felton/pingouins into Dev

AI/src/game/penguin.cpp

@@ -567,4 +567,27 @@ namespace game
         return played;
         
     }
+
+	uint32_t penguin::move_to_pos(uint16_t m)
+	{
+		uint32_t result = 0;
+		uint32_t* peng;
+		uint16_t rel_move = m;
+		int i = 0;
+
+		if(state.current_player_red) {
+			for(i = 0; (i < 3) && (PENGUIN_TOT_MOVES(state.peng_red[i]) <= rel_move); i ++) //While we didn't find the penguin
+				rel_move -= PENGUIN_TOT_MOVES(state.peng_red[i]);
+			peng = &state.peng_red[i];
+		}
+		else {
+			for(i = 0; (i < 3) && (PENGUIN_TOT_MOVES(state.peng_blue[i]) <= rel_move); i ++) //While we didn't find the penguin
+				rel_move -= PENGUIN_TOT_MOVES(state.peng_blue[i]);
+			peng = &state.peng_blue[i];
+		}
+
+		result = PENGUIN_POS(*peng) << 16;
+		play(m);
+		result |= PENGUIN_POS(*peng);
+	}
 }

AI/src/game/penguin.hpp

@@ -84,10 +84,13 @@ namespace game
 			uint8_t turns_played() const;
 			int update_penguin_moves(uint32_t* p, uint64_t obstacles);
 			uint64_t create_obstacles_bitboard();
+			uint32_t move_to_pos(uint16_t m);
+
 
 		private:
 			penguin_state state;
 			void move_penguin(uint32_t* p, uint16_t rel_move);
+			
 
 			const uint8_t RED = 0;
 			const uint8_t BLUE = 1;

AI/src/mcts/test_mcts_two_players.hpp

@@ -87,13 +87,16 @@ template <typename Game>
 void test_mcts_two_players<Game>::save_board(const Game& game, int move){
 	std::shared_ptr<game::penguin> g = game::copy(game);
 	game::penguin_state state = g->get_state();
-	savefile << state.one_fish << ";" << state.two_fish << ";" << state.three_fish << ";" << g->penguin_board(false) << ";" << g->penguin_board(true) << ";" << move << std::endl;
+	uint32_t pos = g->move_to_pos(move);
+	uint16_t peng_pos = (uint16_t)(pos >> 16);
+	uint16_t peng_pos = (uint16_t)pos;
+	savefile << state.one_fish << ";" << state.two_fish << ";" << state.three_fish << ";" << g->penguin_board(false) << ";" << g->penguin_board(true) << ";" << peng_pos << ";" << dest << std::endl;
 }
 
 template <typename Game>
 void test_mcts_two_players<Game>::play(Game g, const heuristic<Game>& h)
 {
-    //    ProfilerStart("theturk.prof");
+    //ProfilerStart("theturk.prof");
     auto the_turk = make_mcts_two_players(g, MCTS_TURN_TIME, 0.4, 8, h);
     std::cout << "play one game" << std::endl;
     std::cout << "who's first? (h)uman/(c)omputer ";

Keras/deeplearning

@@ -4,28 +4,28 @@ from keras.models import Sequential
 from keras.layers import Dense
 
 import numpy
-# fix random seed for reproducibility
+# Fix random seed for reproducibility
 seed = 7
 numpy.random.seed(seed)
 
-# loading data
+# Loading data
 dataset = numpy.loadtxt("save.csv", delimiter=";")
-# split into input (X) and output (Y) variables
+# Split into input (X) and output (Y) variables
 X = dataset[:,0:5]
 Y = dataset[:,5]
 
-# create model
+# Creating the model
 model = Sequential()
 model.add(Dense(12, input_dim=5, init='uniform', activation='relu'))
 model.add(Dense(8, init='uniform', activation='relu'))
-model.add(Dense(1, init='uniform', activation='sigmoid'))
+model.add(Dense(1, init='uniform', activation='softmax'))
 
-# Compile model
-model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
+# Compiling the model
+model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
 
-# Fit the model
-model.fit(X, Y, nb_epoch=150, batch_size=10)
+# Training the model
+model.fit(X, Y, nb_epoch=5, batch_size=10)
 
-# evaluate the model
+# Evaluating the model
 scores = model.evaluate(X, Y)
 print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))

Keras/save.csv

@@ -48,7 +48,6 @@
 234191587400222720;1073746433;64;18014398515773952;4398180732992;0
 234191587400222720;1073746433;64;18014398515773952;4398180732992;0
 234191587400222720;1073742337;64;18014398515773952;4398180730944;0
-931934812694784276;148647583688971945;72339108223090754;19795638484992;576601558511257600;54306
 931934812694784276;148629991502927529;72339108223090754;2203452440592;576601558511257600;38
 931794075206428948;148629991502927529;72339108223090754;2203452440592;576460821022935040;35
 931794075206428948;148629991502927529;72339103928123458;2199157538832;576460821022935040;6