Deeptionary (JS) Nested dictionaries are incredibly powerful functional structures for reinforcement networks, but they can be awfully sloppy to use without polluting the flow representation in the call stack, or causing a stack overflow. This implementation uses a while loop for deep reads/writes instead of recursive function calls to mitigate …

Deeptionary.js

function Deeptionary (Key_Path, Load_From_Dump_Object) {
	var obj = Load_From_Dump_Object || {};
	var ref = function (Read_Write_Path, Write_Function) {
		var path_index = 0;
		var walk_obj = obj;
		switch (Object.keys(arguments).length) {
			case 0: // dump
				return obj;
			case 1: // read
				do {
					walk_obj = walk_obj[Read_Write_Path[path_index]] || {};
					path_index++;
				} while (path_index < Read_Write_Path.length);
				return walk_obj;
			case 2: // write
				do {
					if (!walk_obj.hasOwnProperty(Read_Write_Path[path_index])) walk_obj[Read_Write_Path[path_index]] = {};
					walk_obj = walk_obj[Read_Write_Path[path_index]] || {};
					path_index++;
				} while (path_index < Read_Write_Path.length - 1);
				walk_obj[Read_Write_Path[path_index]] = Write_Function(walk_obj[Read_Write_Path[path_index]]);
				return;
		}
	};
	return ref;
};

// create a new deeptionary {instate: {option: {outstate: {score: {tally: val}}}}}
var D = Deeptionary(['in_state', 'option', 'outstate', 'score', 'tally']);

// create a function that will initialize a value to 0 if it didnt exist then increment it
var incr = function (val) { if (val == null) val = 0; val++; return val; };

// increment a deep state 3 times
D(['myinstate', 'myoption', 'myoutstate', 200], incr);
D(['myinstate', 'myoption', 'myoutstate', 200], incr);
D(['myinstate', 'myoption', 'myoutstate', 200], incr);

// read a deep value 
console.log(D(['myinstate', 'myoption', 'myoutstate', 200]));

// output: 3

// dump whole deeptionary
console.log(JSON.stringify(D(), null, '  '));

// output: {"myinstate": {"myoption": {"myoutstate": {"200": 3}}}}

I enjoyed your heroku tetris game enormously! Thank you so much! Regards, dataanxiety on tumblr

Haha you're welcome, wish I still had the source!