use named parameters for functions that have 3+

fixes #63

Author: GrosSacASac

js/ai/qlearn/examples/dodgeShoot/dodgeShoot.js

@@ -82,9 +82,9 @@ const start = (options) => {
             let actionName;
             if (useIntelligence) {
                 stateActions = reduceStateAndAction(state);
-                actionName = decide(intelligence, stateActions, actionNames);
+                actionName = decide({ intelligence, stateActions, actionNames });
             } else {
-                actionName = randomDecide(actionNames);
+                actionName = randomDecide({ actionNames });
             }
             const action = actions[actionName];
             updateGame(action, state, reward); // reward and changes state
@@ -97,7 +97,14 @@ const start = (options) => {
                 stateActions = reduceStateAndAction(state);
                 const scoreAfter = state.score;
                 const scoreDifference = scoreAfter - scoreBefore;
-                learn(intelligence, previousStateActions, stateActions, actionName, actionNames, scoreDifference);
+                learn({
+                    intelligence,
+                    previousStateActions,
+                    stateActions,
+                    previousAction: actionName,
+                    actionNames,
+                    reward: scoreDifference,
+                });
             }
             state.frame += 1;
             if (state.frame < MAX_FRAMES) {

js/ai/qlearn/examples/eatFoodAvoidDanger/eatFoodAvoidDanger.js

@@ -79,7 +79,7 @@ const step = () => {
     const state = initialState;
     const stateActions = reduceStateAndAction(state);
     const scoreBefore = state.score;
-    const actionName = decide(intelligence, stateActions, actionNames);
+    const actionName = decide({ intelligence, stateActions, actionNames });
     const action = actions[actionName];
     updateGame(action, state); // reward and changes state
     if (display) {
@@ -88,7 +88,14 @@ const step = () => {
     const stateActionsAfter = reduceStateAndAction(state);
     const scoreAfter = state.score;
     const reward = scoreAfter - scoreBefore;
-    learn(intelligence, stateActions, stateActionsAfter, actionName, actionNames, reward);
+    learn({
+        intelligence,
+        previousStateActions: stateActions,
+        stateActions: stateActionsAfter,
+        previousAction: actionName,
+        actionNames,
+        reward,
+    });
     frame += 1;
     if (frame < MAX_FRAMES) {
         scheduleNext(step);

js/ai/qlearn/readme.md

@@ -64,10 +64,10 @@ Will use `.qualityMap`.
 
 
 ```js
-const actionName = decide(intelligence, stateAction, actionNames);
+const actionName = decide({intelligence, stateAction, actionNames});
 ```
 
-Alternatively use partial random decide. It is the same function, except it randomly decides 20% of the time
+Alternatively use partial random decide. It is the same function, except it randomly decides 20% of the time.
 
 ```js
 import { partialRandomDecide } from "qlearn/source/partialRandomDecide.js";
@@ -86,11 +86,14 @@ Will update `.qualityMap`.
 Note: It is possible to learn even if the previous action did not come from `decide()`, for example: If a human decides, the `learn()` can still be used.
 
 ```js
-learn(
+learn({
     intelligence,
-    previousStateActions, stateActions,
-    previousAction, actionNames, reward
-);
+    previousStateActions,
+    stateActions,
+    previousAction,
+    actionNames,
+    reward,
+});
 ```
 
 ### `.qualityMap`

js/ai/qlearn/source/partialRandomDecide.js

@@ -4,7 +4,13 @@ import { randomDecide } from "./randomDecide.js";
 
 
 const defaultRandomRate = 0.2;
-const partialRandomDecide = (intelligence, stateActions, actionNames, randomRate = defaultRandomRate, random = Math.random) => {
+const partialRandomDecide = ({
+    intelligence,
+    stateActions,
+    actionNames,
+    randomRate = defaultRandomRate,
+    random = Math.random,
+}) => {
     if (random() < randomRate) {
         return decide(intelligence, stateActions, actionNames);
     }

js/ai/qlearn/source/qlearn.js

@@ -41,7 +41,7 @@ const averageQuality = (qualityForState) => {
     return average;
 };
 
-const decide = (intelligence, stateActions, actionNames) => {
+const decide = ({ intelligence, stateActions, actionNames }) => {
     const qualityForState = intelligence.qualityMap.get(stateActions);
     if (!qualityForState) {
         return actionNames[0]; // take first (random)
@@ -51,7 +51,14 @@ const decide = (intelligence, stateActions, actionNames) => {
 };
 
 const createLearn = (getNextQualityEstimation) => {
-    return (intelligence, previousStateActions, stateActions, previousAction, actionNames, reward) => {
+    return ({
+        intelligence,
+        previousStateActions,
+        stateActions,
+        previousAction,
+        actionNames,
+        reward,
+    }) => {
         let qualityForState = intelligence.qualityMap.get(previousStateActions);
         if (!qualityForState) {
             // there was no quality map for this set of state and actions

js/ai/qlearn/source/randomDecide.js

@@ -1,6 +1,6 @@
 export { randomDecide };
 
 
-const randomDecide = (actionNames, random = Math.random) => {
+const randomDecide = ({ actionNames, random = Math.random }) => {
     return actionNames[Math.floor(random() * actionNames.length)];
 };