add dino jumping environment, deterministic/reproducable behaviour and save-and-load feature

- add feature to save and load learning progress (Q-Table) and current episode count
- episode end is now purely decided by environment instead of monte carlo algo capping it on 10 actions
- using linkedHashMap on all locations to ensure deterministic behaviour
- fixed major RNG issue to reproduce algorithmic behaviour
- clearing rewardHistory, to only save the last 10k rewards
- added google dino jump environment

src/main/java/example/JumpingDino.java

@@ -0,0 +1,23 @@
+package example;
+
+import core.RNG;
+import core.algo.Method;
+import core.controller.RLController;
+import evironment.jumpingDino.DinoAction;
+import evironment.jumpingDino.DinoWorld;
+
+public class JumpingDino {
+    public static void main(String[] args) {
+        RNG.setSeed(55);
+
+        RLController<DinoAction> rl = new RLController<DinoAction>()
+                .setEnvironment(new DinoWorld())
+                .setAllowedActions(DinoAction.values())
+                .setMethod(Method.MC_ONPOLICY_EGREEDY)
+                .setDiscountFactor(1f)
+                .setEpsilon(0.15f)
+                .setDelay(200)
+                .setEpisodes(100000);
+        rl.start();
+    }
+}