wip: implement score caltulation and action possibilities
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@ -1,9 +1,7 @@
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package uulm.teamname.marvelous.gamelibrary.ai;
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import uulm.teamname.marvelous.gamelibrary.IntVector2;
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import uulm.teamname.marvelous.gamelibrary.config.CharacterConfig;
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import uulm.teamname.marvelous.gamelibrary.config.PartyConfig;
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import uulm.teamname.marvelous.gamelibrary.config.ScenarioConfig;
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import uulm.teamname.marvelous.gamelibrary.entities.EntityID;
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import uulm.teamname.marvelous.gamelibrary.entities.EntityType;
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import uulm.teamname.marvelous.gamelibrary.gamelogic.GameStateView;
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@ -13,15 +11,15 @@ import java.util.HashMap;
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class BoardAnalyzer {
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private final Board origin;
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private final EntityType player;
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private final HashMap<Integer, Integer> cache = new HashMap<>();
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private final HashMap<Integer, Float> cache = new HashMap<>();
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public BoardAnalyzer(GameStateView state, EntityType player) {
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this.origin = Board.generate(state, player);
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this.player = player;
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public BoardAnalyzer(GameStateView state, EntityID turn) {
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this.origin = Board.generate(state, turn);
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this.player = turn.type;
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}
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public Action analyze(IntVector2 position, EntityType turn, PartyConfig partyConfig, CharacterConfig characterConfig, ScenarioConfig scenarioConfig) {
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ArrayList<Action> actions = origin.generateActions();
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public Action analyze(GameStateView state, IntVector2 position, EntityID turn) {
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ArrayList<Action> actions = origin.generateActions(state);
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//TODO: create minimax tree
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