Compare commits

...

5 Commits

  1. 54
      css/src/style.scss
  2. 77
      css/style.css
  3. 2
      css/style.min.css
  4. BIN
      img/robot.png
  5. BIN
      img/station.png
  6. 73
      index.html
  7. 2
      js/controls.js
  8. 57
      js/rl.js
  9. 904
      js/view.js

@ -1,9 +1,13 @@
// compileCompressed
*{
margin: 0;
padding: 0;
}
body{
margin: 0;
padding: 0;
// background-color: ;
font-family: sans-serif;
}
#container{
height: 100vh;
@ -12,17 +16,30 @@ body{
#canvas{
height: 100%;
}
nav{
position: absolute;
top: 10px;
left: 10px;
}
button{
margin: 0.3em;
}
.absolute{
position: absolute;
top:0;
left:0;
}
.stage{
display: flex;
justify-content: center;
align-items: center;
height: 100vh;
}
.plot{
position: absolute;
top: 2vh;
@ -30,3 +47,40 @@ nav{
width: 20vw;
height: 10vw;
}
.sliders{
position: absolute;
top: 20vh;
left: 2vw;
width: 20vw;
}
#formula{
position: absolute;
top: 71.5vh;
width: 90vw;
}
.score{
position: absolute;
top: 7vh;
left: 2vw;
width: 20vw;
}
.lightbox{
padding: 2em;
position: absolute;
top:0;
left: 50%;
transform: translateX(-50%) translateY(-100%);
z-index: 10;
max-width: 50%;
background-color: #BBB;
transition: all 1s;
&.active{
top:20%;
transform: translateX(-50%) translateY(-50%);
}
}

@ -0,0 +1,77 @@
* {
margin: 0;
padding: 0;
}
body {
margin: 0;
padding: 0;
font-family: sans-serif;
}
#container {
height: 100vh;
position: relative;
}
#canvas {
height: 100%;
}
nav {
position: absolute;
top: 10px;
left: 10px;
}
.absolute {
position: absolute;
top: 0;
left: 0;
}
.plot {
position: absolute;
top: 2vh;
right: 2vw;
width: 20vw;
height: 10vw;
}
.sliders {
position: absolute;
top: 20vh;
left: 2vw;
width: 20vw;
}
#formula {
position: absolute;
top: 71.5vh;
width: 90vw;
}
.score {
position: absolute;
top: 7vh;
left: 2vw;
width: 20vw;
}
.lightbox {
padding: 2em;
position: absolute;
top: 0;
left: 50%;
transform: translateX(-50%) translateY(-100%);
z-index: 10;
width: 50%;
height: 40%;
background-color: #BBB;
transition: all 1s;
}
.lightbox.active {
top: 50%;
transform: translateX(-50%) translateY(-50%);
}

2
css/style.min.css vendored

@ -1 +1 @@
*{margin:0;padding:0}#container{height:100vh;position:relative}#canvas{height:100%}nav{position:absolute;top:10px;left:10px}.absolute{position:absolute;top:0;left:0}.plot{position:absolute;top:2vh;right:2vw;width:20vw;height:10vw}
*{margin:0;padding:0}body{margin:0;padding:0;font-family:sans-serif}#container{height:100vh;position:relative}#canvas{height:100%}nav{position:absolute;top:10px;left:10px}button{margin:0.3em}.absolute{position:absolute;top:0;left:0}.stage{display:flex;justify-content:center;align-items:center;height:100vh}.plot{position:absolute;top:2vh;right:2vw;width:20vw;height:10vw}.sliders{position:absolute;top:20vh;left:2vw;width:20vw}#formula{position:absolute;top:71.5vh;width:90vw}.score{position:absolute;top:7vh;left:2vw;width:20vw}.lightbox{padding:2em;position:absolute;top:0;left:50%;transform:translateX(-50%) translateY(-100%);z-index:10;max-width:50%;background-color:#BBB;transition:all 1s}.lightbox.active{top:20%;transform:translateX(-50%) translateY(-50%)}

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@ -3,49 +3,62 @@
<head>
<meta charset="utf-8">
<script src="https://unpkg.com/konva@4.0.0/konva.min.js"></script>
<script src='https://unpkg.com/vue/dist/vue.js'></script>
<script src='https://unpkg.com/vue/dist/vue.min.js'></script>
<script src='https://cdn.jsdelivr.net/npm/vue-konva@2.0.11/umd/vue-konva.min.js'></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/gsap/1.20.3/TweenMax.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.7.1/Chart.min.js"></script>
<script src="https://unpkg.com/vue-chartjs@3.4.2/dist/vue-chartjs.js"></script>
<script src="https://cdn.jsdelivr.net/npm/vue-slider-component@3.0.41/dist/vue-slider-component.umd.min.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/vue-slider-component@3.0.41/theme/default.css">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.11.1/dist/katex.min.css" integrity="sha384-zB1R0rpPzHqg7Kpt0Aljp8JPLqbXI3bhnPWROx27a9N0Ll6ZP/+DiW/UqRcLbRjq" crossorigin="anonymous">
<!-- The loading of KaTeX is deferred to speed up page rendering -->
<script src="https://cdn.jsdelivr.net/npm/katex@0.11.1/dist/katex.min.js" integrity="sha384-y23I5Q6l+B6vatafAwxRu/0oK/79VlbSz7Q9aiSZUvyWYIYsd+qj+o24G5ZU2zJz" crossorigin="anonymous"></script>
<title>RL exhibit - prototype</title>
<link rel="stylesheet" href="https://gitcdn.xyz/cdn/jzilg/embellish.css/fff9961c5fec2d1c8ff53c87b12e18d5c8db7761/embellish.min.css">
<link rel="stylesheet" href="css/style.min.css">
</head>
<body>
<div id="app">
<v-stage ref="stage" :config="stage_config">
<!-- <v-layer ref="local_layer" :config="local_layer">
<v-group ref="map_group" :config="map_config">
<v-rect v-for="(t_type, idx) in maze.map.flat()" :config="get_tile_config(idx, t_type, true)" :key="idx"></v-rect>
<v-regular-polygon :config="agent_config"></v-regular-polygon>
</v-group>
</v-layer> -->
<v-layer ref="map_layer">
<v-group ref="mini_map_group" :config="mini_map_config">
<!-- <v-group ref="grid_group">
<v-line v-for="y in maze.height+1" :config="get_grid_line_config(y-1, true)"></v-line>
<v-line v-for="x in maze.width+1" :config="get_grid_line_config(x-1)"></v-line>
</v-group> -->
<v-rect v-for="(t_type, idx) in maze.map.flat()" :config="get_tile_config(idx, t_type)" :key="idx"></v-rect>
<v-regular-polygon :config="agent_config"></v-regular-polygon>
</v-group>
</v-layer>
</v-stage>
<line-chart css-classes="plot" :chart-data="datacollection" :options="{responsive: true, maintainAspectRatio: false,scales: {xAxes: [{ticks:{maxTicksLimit:11}}]},legend: {display: false}}"></line-chart>
<rl-local class="stage" :machine="machine" :maze="maze" :config="stage_config" v-show="isActive('local')"></rl-local>
<rl-map class="stage" :machine="machine" :maze="maze" :config="stage_config" v-show="isActive('global')"></rl-map>
<line-chart css-classes="plot" :chart-data="datacollection" :options="plot_options" v-show="isActive('plot')"></line-chart>
<div class="sliders" v-show="isActive('sliders')">
<h1>Learning Rate {{machine.learning_rate}}</h1>
<vue-slider v-model="machine.learning_rate" :drag-on-click="true" v-bind="slider_config"></vue-slider>
<h1>Discount Factor {{machine.discount_factor}}</h1>
<vue-slider v-model="machine.discount_factor" :drag-on-click="true" v-bind="slider_config"></vue-slider>
<h1>Epsilon {{machine.epsilon}}</h1>
<vue-slider v-model="machine.epsilon" :drag-on-click="true" v-bind="slider_config"></vue-slider>
<div id="formula"></div>
</div>
<div class="score" v-show="isActive('score')">
<h1>Current Energy</h1>
<h2>{{machine.score}}</h2>
</div>
<navi-gation :options="navigation" v-show="isActive('navi')"></navi-gation>
</div>
<nav>
<button class="button" onclick="machine.run(1)">run 100 episodes!</button>
<button class="button" onclick="machine.auto_step();">auto step!</button>
<button class="button" onclick="machine.greedy_step();">greedy step!</button>
</nav>
<script>
var map = [
[0, 0, 4, 8, 0, 0, 0, 0],
[0, 0, 4, 4, 4, 4, 0, 0],
[4, 0, 0, 0, 0, 4, 0, 4],
[0, 0, 1, 0, 0, 0, 0, 0],
[2, 0, 1, 0, 4, 0, 0, 4]
[0, 0, 1, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[1, 0, 0, 0, 0, 1, 0, 1, 0, 1],
[0, 0, 0, 1, 0, 0, 0, 1, 0, 1],
[0, 1, 1, 1, 1, 1, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1, 0, 0],
[1, 0, 1, 0, 0, 0, 0, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0, 0, 0, 0],
[2, 0, 0, 0, 1, 0, 1, 0, 0, 1]
];
</script>
<script src="js/rl.js"></script>

2
js/controls.js vendored

@ -27,7 +27,7 @@ function key_callback(e) {
break;
}
var ret = 1;
if (tmp != undefined){
if (tmp != undefined && document.querySelector(".lightbox.active") == null){
ret = machine.step(tmp);
}
// show_q_table();

@ -4,36 +4,53 @@ class RL_machine {
rewards,
start_state,
end_states,
start_score,
end_score,
learning_rate,
discount_factor,
epsilon=0) {
this.q_table = actions_per_state.map((c) => c.reduce((o,n) => {o[n]=0; return o},{}));
this.actions_per_state = actions_per_state;
this.transactions = transactions;
this.rewards = rewards;
this.lr = learning_rate;
this.df = discount_factor;
this.state = start_state;
this.start_state = start_state;
this.start_score = start_score;
this.end_score = end_score;
this.end_states = end_states;
this.episode = 0;
this.epsilon = epsilon;
this.score = 0;
this.running = false;
this.score_history = [];
this.q_table = this.actions_per_state.map((c) => c.reduce((o,n) => {o[n]=0; return o},{}));
this.reset_machine();
this.callback = null;
}
setCallback(cb){
this.callback = cb;
}
reset_machine(){
this.q_table = this.q_table.map((c) => c.map((a) => a.fill(0)));
for (var q in this.q_table){
for (var key in this.q_table[q]){
this.q_table[q][key] = 0;
}
}
this.episode = 0;
this.running = false;
this.score_history = [];
this.state = this.start_state;
this.score = this.start_score;
}
new_episode(){
new_episode(reason = "failed"){
const reset = () => {
this.episode++;
this.score_history.push(this.score);
this.state = this.start_state;
this.score = this.start_score;
}
// add_new_episode_callback
this.episode++;
this.state = this.start_state;
this.score_history.push(this.score);
this.score = 0;
if (!this.running && this.callback) {
this.callback(reason).then((p) => reset());
} else {
reset();
}
}
auto_step(){
if (Math.random() < this.epsilon){
@ -48,8 +65,12 @@ class RL_machine {
step(action){
this.state = this.update_q_table(this.state, action);
// add_new_step_callback
if (this.end_states.indexOf(this.state) >= 0 || this.score < this.end_score){
this.new_episode();
if (this.end_states.indexOf(this.state) >= 0) {
this.new_episode("success");
return 2
}
if (this.score <= this.end_score){
this.new_episode("failed");
return 2
}
return 1
@ -127,6 +148,10 @@ class Maze {
for (let idy=0; idy<this.map.length; idy++){
for (let idx=0; idx<this.map[0].length; idx++){
var action = [];
if (this.map[idy][idx] == tile.wall){
actions.push(action);
continue;
}
if (idy != 0){
if(this.map[idy-1][idx] != tile.wall){
action.push(dir.UP);
@ -177,10 +202,10 @@ class Maze {
}
}
const reward = {[tile.regular]:-1,[tile.dangerous]:-1000,[tile.end]:1000,[tile.start]:-1};
const reward = {[tile.regular]:-1,[tile.dangerous]:-100,[tile.end]:1000,[tile.start]:-1};
var maze = new Maze(map, reward);
var learning_rate = 0.75;
var discount_factor = 0.8;
var machine = new RL_machine(maze.actions, maze.transactions, maze.rewards, maze.start_state, maze.end_states, -999, learning_rate, discount_factor, 0.2);
var machine = new RL_machine(maze.actions, maze.transactions, maze.rewards, maze.start_state, maze.end_states, 50, 0, learning_rate, discount_factor, 0.2);

@ -1,264 +1,156 @@
// ----------------------------------------------------------------------------
// ------------------------------- Utils --------------------------------------
// ----------------------------------------------------------------------------
function defer() {
var res, rej;
var promise = new Promise((resolve, reject) => {
res = resolve;
rej = reject;
});
promise.resolve = res;
promise.reject = rej;
return promise;
}
// ----------------------------------------------------------------------------
// -------------------------------- Plot --------------------------------------
// ----------------------------------------------------------------------------
Array.prototype.simpleSMA = function(N) {
return this.map(
function(el, index, _arr) {
return _arr.filter(
function(x2, i2) {
return i2 <= index && i2 > index - N;
})
.reduce(
function(last, current, index, arr) {
return (current / arr.length + last);
}, 0);
});
};
Array.prototype.max = function() {
return this.map(
function(el, index, _arr) {
return _arr.filter(
function(x2, i2) {
return i2 <= index;
})
.reduce(
function(last, current) {
return last > current ? last : current;
}, -1000000000);
});
};
Vue.component('line-chart', {
extends: VueChartJs.Line,
mixins: [VueChartJs.mixins.reactiveProp],
props: ['options'],
// mixins: [VueChartJs.mixins.reactiveData],
// props: ['options','labels', 'datasets'],
// watch: {
// 'labels': function(new_val) {
// this.chartData = {
// 'labels': new_val,
// 'datasets': this.datasets};
// },
// 'datasets': {
// deep:true,
// handler: function(new_val) {
// this.chartData = {
// 'labels': this.labels,
// 'datasets': new_val};
// }
// }
// },
mounted () {
mounted() {
this.renderChart(this.chartData, this.options);
},
})
Array.prototype.simpleSMA=function(N) {
return this.map(
function(el,index, _arr) {
return _arr.filter(
function(x2,i2) {
return i2 <= index && i2 > index - N;
})
.reduce(
function(last, current,index, arr){
return (current/arr.length + last);
},0);
});
};
Array.prototype.max=function() {
return this.map(
function(el,index, _arr) {
return _arr.filter(
function(x2,i2) {
return i2 <= index;
})
.reduce(
function(last, current){
return last > current ? last:current;
},-1000000000);
});
};
// ----------------------------------------------------------------------------
// --------------------------------- Map --------------------------------------
// ----------------------------------------------------------------------------
app = new Vue({
el: '#app',
data: {
width: 0,
height: 0,
q_table: machine.q_table,
maze: maze,
state: {x:0,y:0},
state_tween: new TimelineLite(),
score: machine.score,
score_history: machine.score_history,
labels: [],
var MapBase = Vue.component('MapBase', {
props: ['machine', 'maze', 'config'],
data: function () {
return {
robot_image: null,
energy_image: null,
}
},
created() {
// Resize handler
window.addEventListener('resize', this.handleResize)
this.handleResize();
// State wrapper
var s = machine.state;
var $this = this;
this.state = this.s2p(s);
Object.defineProperty(machine, 'state', {
get: function() { return this._state },
set: function(ne) { this._state=ne; $this.handleState(this._state); }
});
machine.state = s;
// Score wrapper
var s = machine.score;
var $this = this;
this.score = s;
Object.defineProperty(machine, 'score', {
get: function() { return this._score },
set: function(ne) { this._score=ne; $this.score=ne}
});
machine.score = s;
// Score history wrapper
var s = machine.score_history;
var $this = this;
this.score_history = s;
Object.defineProperty(machine, 'score_history', {
get: function() { return this._score_history },
set: function(ne) { this._score_history=ne; $this.score_history=ne}
});
machine.score_history = s;
},
destroyed() {
window.removeEventListener('resize', this.handleResize)
const robot_image = new window.Image();
robot_image.src = "img/robot.png";
robot_image.onload = () => {
$this.robot_image = robot_image;
};
const energy_image = new window.Image();
energy_image.src = "img/station.png";
energy_image.onload = () => {
$this.energy_image = energy_image;
};
},
computed: {
datacollection: function () {
main_config: function(){
return {
labels: Array.from(Array(this.score_history.length).keys()),
datasets: [
{
label: 'Data One',
backgroundColor: 'rgb(0,0,0,0)',
data: this.score_history.simpleSMA(Math.round(50)),
fill: false,
borderColor: 'rgb(255, 159, 64)',
pointRadius: 1,
},
{
label: 'Data One',
backgroundColor: 'rgb(0,0,0,0)',
data: this.score_history.max(),
fill: false,
borderColor: 'rgb(64, 159, 255)',
pointRadius: 1,
},
]
}
},
stage_config: function () {
return {
width: this.width,
height: this.height,
}
},
mini_map_config: function () {
return {
x:this.width/2-(this.base_size*(this.maze.width)/2),
y:this.height/2-(this.base_size*(this.maze.height)/2),
scale:{
x: 1,
y: 1
}
}
},
local_layer: function () {
return {
x: this.width/2,
y: this.height/2,
scale:{
x: 2,
y: 2
offset: {
x: -(this.config.width-this.base_size*this.maze.width)/2,
y: -(this.config.height-this.base_size*this.maze.height)/2,
}
}
},
map_config: function () {
robot_config: function() {
return {
x: this.base_size*(this.maze.width-this.state.x),
y: this.base_size*(this.maze.height-this.state.y),
offset: {
x: this.base_size*this.maze.width+this.base_size/2,
y: this.base_size*this.maze.height+this.base_size/2,
height: this.base_size,
width: this.base_size,
x: this.center,
y: this.center,
image: this.robot_image,
offset:{
x: this.base_size/2,
y: this.base_size/2,
}
}
},
agent_config: function () {
energy_config: function() {
return {
sides: 5,
radius: this.base_size / 3,
fill: '#00D2FF',
stroke: 'black',
strokeWidth: this.strokeW,
height: this.base_size,
width: this.base_size,
offset: {
x: -this.base_size / 2,
y: -this.base_size / 2
x: this.base_size/2,
y: this.base_size/2
},
x: this.base_size*this.state.x,
y: this.base_size*this.state.y,
image: this.energy_image,
}
},
base_size: function () {
return Math.min(this.stage_config.height * 0.8 / this.maze.height, this.stage_config.width * 0.5 / this.maze.width);
},
strokeW: function () {
strokeW: function() {
return this.base_size / 50;
},
base_size: function() {
return Math.min(this.config.height/this.maze.height, this.config.width/this.maze.width);
},
},
methods: {
s2p: function(state){
return {
x: (state%this.maze.width),
y: Math.floor(state/this.maze.width),
}
},
p2s: function(x,y){
return x+y*this.maze.width;
},
handleResize: function() {
this.width = window.innerWidth;
this.height = window.innerHeight;
},
handleState: function(s) {
if (!machine.running){
this.state_tween.to(this.state, 0.2, { x: this.s2p(s).x, y: this.s2p(s).y });
} else {
this.state = this.s2p(s);
}
// this.hidden_state = s;
},
get_grid_line_config: function (idx, y=false) {
var offset = this.strokeW/2;
if (y){
var points = [-offset, Math.round(idx * this.base_size), this.base_size * this.maze.width + offset,Math.round(idx * this.base_size)];
} else {
var points = [Math.round(idx * this.base_size), -offset, Math.round(idx * this.base_size), this.base_size * this.maze.height + offset];
}
return {
points: points,
stroke: '#ddd',
strokeWidth: this.strokeW,
}
},
get_tile_type: function (state){
var pos = this.s2p(state);
if (pos.y > maze.height){
get_tile_type: function(state) {
var pos = this.machine.s2p(state);
if (pos.y > maze.height) {
return null;
} else if (pos.x > maze.width){
} else if (pos.x > maze.width) {
return null;
} else {
return maze.map[pos.y][pos.x];
}
},
in_plus: function (pos1, pos2) {
if (Math.abs(pos1.x-pos2.x) + Math.abs(pos1.y-pos2.y) < 2) {
return true;
get_field_config: function(state) {
var pos = this.machine.s2p(state);
return {
x: this.base_size * pos.x+this.base_size/2,
y: this.base_size * pos.y+this.base_size/2,
}
return false;
},
get_tile_config: function (i, t_type, local=false) {
var pos = this.s2p(i);
var over = {};
// not in plus
if (local) {
if (!this.in_plus(this.s2p(i),{x:Math.round(this.state.x),y:Math.round(this.state.y)})) {
over = {
opacity: 0,
fill: "#eee"
};
} else if (i != this.p2s(Math.round(this.state.x),Math.round(this.state.y))) {
over = {
opacity: 1,
fill: "#eee"
};
}
}
get_tile_config: function(t_type) {
const layout = {
x: this.base_size * pos.x,
y: this.base_size * pos.y,
width: this.base_size,
height: this.base_size,
stroke: '#ddd',
strokeWidth: this.strokeW,
offset: {
x: this.base_size/2,
y: this.base_size/2,
}
};
switch (t_type) {
case tile.regular:
@ -266,37 +158,607 @@ app = new Vue({
...layout,
fill: '#fff',
opacity: 1,
...over,
}
case tile.end:
return {
...layout,
fill: '#0eb500',
opacity: 1,
...over,
}
case tile.start:
return {
...layout,
fill: '#ff0008',
opacity: 1,
...over,
}
case tile.dangerous:
return {
...layout,
fill: '#FF7B17',
opacity: 1,
...over,
}
case tile.wall:
return {
...layout,
fill: '#000000',
opacity: 1,
...over,
}
}
},
},
})
//-----------------------------------------------------------------------------
var palette = ['#d2000d', '#d30512', '#d40a17', '#d50f1c', '#d61420', '#d71a25', '#d71f2a', '#d8242f', '#d92934', '#da2e39', '#db333d', '#dc3842', '#dd3d47', '#de424c', '#df4751', '#e04d56', '#e0525a', '#e1575f', '#e25c64', '#e36169', '#e4666e', '#e56b73', '#e67077', '#e7757c', '#e87a81', '#e98086', '#e9858b', '#ea8a90', '#eb8f95', '#ec9499', '#ed999e', '#ee9ea3', '#efa3a8', '#f0a8ad', '#f1adb2', '#f2b3b6', '#f2b8bb', '#f3bdc0', '#f4c2c5', '#f5c7ca', '#f6cccf', '#f7d1d3', '#f8d6d8', '#f9dbdd', '#fae0e2', '#fbe6e7', '#fbebec', '#fcf0f0', '#fdf5f5', '#fefafa', '#ffffff', '#fafcfa', '#f5f9f5', '#f0f6f0', '#ebf3ec', '#e6f1e7', '#e1eee2', '#dcebdd', '#d7e8d8', '#d3e5d3', '#cee2cf', '#c9dfca', '#c4dcc5', '#bfd9c0', '#bad6bb', '#b5d4b6', '#b0d1b2', '#abcead', '#a6cba8', '#a1c8a3', '#9cc59e', '#97c299', '#92bf95', '#8dbc90', '#88b98b', '#84b786', '#7fb481', '#7ab17c', '#75ae77', '#70ab73', '#6ba86e', '#66a569', '#61a264', '#5c9f5f', '#579c5a', '#529a56', '#4d9751', '#48944c', '#439147', '#3e8e42', '#398b3d', '#348839', '#308534', '#2b822f', '#267f2a', '#217d25', '#1c7a20', '#17771c', '#127417', '#0d7112', '#086e0d']
Vue.component('rl-map', {
extends: MapBase,
computed: {
robot_config: function() {
return {
height: this.base_size,
width: this.base_size,
x: this.base_size * this.machine.state.x,
y: this.base_size * this.machine.state.y,
image: this.robot_image,
}
},
extreme_q_values: function(){
var max = -10*30;
var min = 10*30;
for (field in this.q_table) {
for (key in this.q_table[field]){
if (this.q_table[field][key]<min){
min = this.q_table[field][key];
} else if (this.q_table[field][key]>max){
max = this.q_table[field][key];
}
}
}
return {min: min, max: max};
}
},
methods: {
get_q_text_config: function (val, i) {
var off, key;
switch (i) {
case 1:
off = {
align: "center",
verticalAlign: "top",
};
key = dir.UP;
break;
case 2:
off = {
align: "right",
verticalAlign: "middle",
};
key = dir.RIGHT;
break;
case 3:
off = {
align: "center",
verticalAlign: "bottom",
};
key = dir.DOWN;
break;
case 4:
off = {
align: "left",
verticalAlign: "middle",
};
key = dir.LEFT;
break;
}
if (val[key] === undefined) {
return {}
}
return {
fontSize: this.base_size/7,
fontFamily: 'Calibri',
fill: 'black',
text: +val[key].toPrecision(3)+'',
width: this.base_size-20,
height: this.base_size-34,
...off,
offset: {
x: (this.base_size-20)/2,
y: (this.base_size-34)/2,
}
}
},
get_triangle_config: function(value, d) {
var rot = 0;
switch (d) {
case dir.UP:
rot = -90;
break;
case dir.RIGHT:
rot = 0;
break;
case dir.DOWN:
rot = 90;
break;
case dir.LEFT:
rot = 180;
break;
}
var $this = this;
var norma_value = value>0 ? (value+1000)/(2000) : (value+30)/60;
return {
sceneFunc: function(context, shape) {
context.beginPath();
var width = $this.base_size / 5;
var arrow_w = $this.base_size / 2;
var stumpf = $this.base_size / 6;
var arrow_l = $this.base_size / 5;
context.moveTo($this.base_size/2-stumpf-arrow_l, width/2);
context.lineTo($this.base_size/2-stumpf, width/2);
context.lineTo($this.base_size/2-stumpf, arrow_w/2);
context.lineTo($this.base_size/2-2, 0);
context.lineTo($this.base_size/2-stumpf, -arrow_w/2);
context.lineTo($this.base_size/2-stumpf, -width/2);
context.lineTo($this.base_size/2-stumpf-arrow_l, -width/2);
context.lineTo($this.base_size/2-stumpf-arrow_l, width/2);
context.closePath();
// (!) Konva specific method, it is very important
context.fillStrokeShape(shape);
},
fill: palette[Math.round(norma_value*100)],
stroke: 'black',
strokeWidth: 1,
rotation: rot,
}
},
},
template:
`<v-stage ref="stage" :config="config">
<v-layer ref="map_layer" :config="main_config">
<v-group ref="map_group">
<v-group :key="'tile'+idx" v-for="(t_type, idx) in maze.map.flat()" :config="get_field_config(idx)">
<v-rect :config="get_tile_config(t_type)"></v-rect>
<v-image :config="energy_config" v-if="t_type==8"></v-image>
</v-group>
<v-group :key="'qgroup'+idx" v-for="(action, idx) in machine.q_table" :config="get_field_config(idx)">
<v-shape :key="'qvalshape'+idx+key" v-for="(value, key) in action" :config="get_triangle_config(value, key)"></v-shape>
<v-text :key="'qval'+idx+i" v-for="i in 4" :config="get_q_text_config(action,i)"></v-text>
</v-group>
<v-image :config="robot_config"></v-image>
</v-group>
</v-layer>
</v-stage>`
})
// ----------------------------------------------------------------------------
// -------------------------------- Local -------------------------------------
// ----------------------------------------------------------------------------
Vue.component('rl-local', {
extends: MapBase,
computed: {
main_config: function(){
return {
offset: {
x: -(this.config.width-this.base_size*3)/2,
y: -(this.config.height-this.base_size*3)/2,
}
}
},
local_config: function() {
return {
x: -(this.machine.state.x)*this.base_size,
y: -(this.machine.state.y)*this.base_size,
offset: {
x: -this.base_size,
y: -this.base_size,
}
}
},
base_size: function() {
return Math.min(this.config.height/3, this.config.width/3);
},
center: function() {
return 3*this.base_size / 2;
},
local_area: function() {
const x = Math.round(this.machine.state.x);
const y = Math.round(this.machine.state.y);
let arr = [[x,y-1],[x+1,y],[x,y+1],[x-1,y],[x,y]];
return arr.filter((p) => p[0] < this.maze.width && p[1] < this.maze.height &&
p[0] >= 0 && p[1] >= 0)
.map((p) => [this.maze.map[p[1]][p[0]], p[1]*this.maze.width+p[0]]);
},
},
methods: {
end: function(pos){
return this.maze.get_states(tile.end).indexOf(pos) >= 0;
},
id_to_dir: function(id){
switch (id) {
case 0:
return dir.UP;
case 1:
return dir.RIGHT;
case 2:
return dir.DOWN;
case 3:
return dir.LEFT;
default:
return undefined;
}
},
handleMouseEnter(e) {
const stage = e.target.getStage();
stage.container().style.cursor = "pointer";
},
handleMouseLeave(e) {
const stage = e.target.getStage();
stage.container().style.cursor = "default";
},
get_local_tile_config: function(i, t_type) {
// var pos = this.s2p(i);
// in plus
var over = {};
if (i != this.machine.p2s(Math.round(this.machine.state.x), Math.round(this.machine.state.y)) &&
t_type != tile.wall) {
over = {
width: this.base_size,
height: this.base_size,
stroke: '#ddd',
strokeWidth: this.strokeW,
offset: {
x: this.base_size/2,
y: this.base_size/2,
},
opacity: 1,
fill: "#eee",
}
}
return over;
},
},
template:
`<v-stage ref="stage" :config="config">
<v-layer ref="map_layer" :config="main_config">
<v-group ref="map_group" :config="local_config">
<v-group :key="pair[1]" v-for="(pair, idx) in local_area" :config="get_field_config(pair[1])">
<v-rect :config="get_tile_config(pair[0])"></v-rect>
<v-image :config="energy_config" v-if="end(pair[1])"></v-image>
<v-rect :config="get_local_tile_config(pair[1], pair[0])" @click="id_to_dir(idx) && machine.object.step(id_to_dir(idx))" @mouseenter="handleMouseEnter" @mouseleave="handleMouseLeave"></v-rect>
</v-group>
</v-group>
<v-image :config="robot_config"></v-image>
</v-layer>
</v-stage>`
})
Vue.component('navi-gation', {
props: ["options"],
template: `
<nav class="navi">
<button v-for="(item, key) in options" v-on:click="item">{{ key }}</button>
</nav>`
});
// ----------------------------------------------------------------------------
// ------------------------------ lightbox ------------------------------------
// ----------------------------------------------------------------------------
var light_box = {
data: {
content: "",
options: [],
active: false,
},
methods:{
close: function(){
this.active = false;
},
popup: function(content, options){
this.content = content;
var answer = defer();
var $this = this;
this.options = options.reduce((old, opt) => {
old[opt] = function(){
$this.active = false;
answer.resolve(opt);
}
return old
}, {});
this.active = true;
return answer;
}
},
template: `
<div class="lightbox" v-bind:class="{ active: active }">{{ content }}
<div class="options">
<button :key="key" v-for="(item, key) in options" v-on:click="item">{{ key }}</button>
</div>
</div>`
}
const PopupLibrary = {
install(Vue, options = {}) {
const root = new Vue(light_box)
// Mount root Vue instance on new div element added to body
root.$mount(document.body.appendChild(document.createElement('div')))
Vue.prototype.$lightbox = root;
}
}
window.Vue.use(PopupLibrary)
// ----------------------------------------------------------------------------
// -------------------------------- Main --------------------------------------
// ----------------------------------------------------------------------------
function makeMachineReactive(th, machine){
var $this = th;
$this.machine.s2p = function(state) {
return {
x: (state % $this.maze.width),
y: Math.floor(state / $this.maze.width),
}
};
$this.machine.p2s = function(x, y) {
return x + y * $this.maze.width;
};
// Score wrapper
var s = machine.score;
$this.machine.score = s;
Object.defineProperty(machine, 'score', {
get: function() {
return this._score
},
set: function(ne) {
this._score = ne;
$this.machine.score = ne
}
});
machine.score = s;
// Score history wrapper
var s = machine.score_history;
$this.machine.score_history = s;
Object.defineProperty(machine, 'score_history', {
get: function() {
return this._score_history
},
set: function(ne) {
this._score_history = ne;
$this.machine.score_history = ne
}
});
machine.score_history = s;
// State wrapper
var s = machine.state;
$this.machine.state = $this.machine.s2p(s);
Object.defineProperty(machine, 'state', {
get: function() {
return this._state
},
set: function(ne) {
this._state = ne;
$this.handleState(this._state);
}
});
machine.state = s;
$this.machine.object.setCallback($this.onNewEpisode);
}
app = new Vue({
el: '#app',
components: {
VueSlider: window['vue-slider-component'],
},
data: {
state: null,
maze: maze,
machine: {
object: machine,
q_table: machine.q_table,
state: {
x:0,
y:0,
},
state_tween: new TimelineLite(),
learning_rate: machine.lr,
discount_factor: machine.df,
epsilon: machine.epsilon,
score: machine.score,
score_history: machine.score_history,
s2p: null,
p2s: null,
},
width: 0,
height: 0,
components: [],
navigation: {},
},
created() {
// Resize handler
window.addEventListener('resize', this.handleResize)
this.handleResize();
makeMachineReactive(this, machine);
this.state = "init";
},
destroyed() {
window.removeEventListener('resize', this.handleResize)
},
computed: {
stage_config: function() {
return {
x: 0,
y: 0,
width: this.width*0.5,
height: this.height*0.8,
}
},
slider_config: function(){
return {
min: 0,
max: 1,
duration: 0,
interval: 0.01,
tooltip: 'none'
}
},
datacollection: function() {
return {
labels: Array.from(Array(this.machine.score_history.length).keys()),
datasets: [{
label: 'Data One',
backgroundColor: 'rgb(0,0,0,0)',
data: this.machine.score_history,//.simpleSMA(Math.round(50)),
fill: false,
borderColor: 'rgb(255, 159, 64)',
pointRadius: 1,
},
// {
// label: 'Data One',
// backgroundColor: 'rgb(0,0,0,0)',
// data: this.score_history.max(),
// fill: false,
// borderColor: 'rgb(64, 159, 255)',
// pointRadius: 1,
// },
]
}
},
plot_options: function() {
var $this = this;
return {
responsive: true,
maintainAspectRatio: false,
scales: {
xAxes: [{
// type: 'linear',
ticks: {
maxTicksLimit: 8,
maxRotation: 0,
}
}]
},
legend: {
display: false
}
}
},
},
methods: {
onEnterState: function(){},
onLeaveState: function(){},
handleState: function(s) {
if (!this.machine.object.running) {
this.machine.state_tween.to(this.machine.state, 0.2, {
x: this.machine.s2p(s).x,
y: this.machine.s2p(s).y
});
} else {
this.machine.state = this.machine.s2p(s);
}
},
handleResize: function() {
this.width = window.innerWidth;
this.height = window.innerHeight;
},
isActive: function(what){
return this.components.indexOf(what) >= 0;
},
changeState: function(state){
this.components = [];
this.navigation = {};
this.onEnterState = function(){};
this.onLeaveState = function(){};
this.state = state;
},
onNewEpisode: function(result){
var text;
if (result == "failed"){
text = "Out of battery. The robot will be resetted.";
} else if (result == "success"){
text = "You reached the goal. The robot will be resetted.";
}
return this.$lightbox.popup(text, ["ok"]);
}
},
watch: {
'machine.learning_rate': function(new_val) {
machine.lr = new_val;
renderLatex();
},
'machine.discount_factor': function(new_val) {
machine.df = new_val;
renderLatex();
},
'machine.epsilon': function(new_val) {
machine.epsilon = new_val;
},
state: function(state){
this.onLeaveState();
Object.assign(this, StateMgr[state]);
this.onEnterState();
},
}
})
function renderLatex() {
// (1-lr) * Q[state, action] + lr * (reward + gamma * np.max(Q[new_state, :])
katex.render(`Q(s,a)\\leftarrow${(1-machine.lr).toFixed(2)}Q(s,a)+${machine.lr.toFixed(2)}(reward + ${machine.df.toFixed(2)}\\max_{a'}(Q(s_{new}, a'))`, document.getElementById('formula'),{displayMode: true,});
}
renderLatex();
// ----------------------------------------------------------------------------
// ------------------------------ StateMgr ------------------------------------
// ----------------------------------------------------------------------------
var StateMgr = {
init: {
onEnterState: function () {
var lightText = `Reinforcement learning (RL) is an area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. (wikipedia)
This exhibit explains how a robot can learn to navigate through a maze in order to reach its destination, before running out of power. At first the robot knows nothing, and learns from each new action (movement) and state (location reached). Slowly it starts to develop an understanding of the maze that will allow it to reach the charging station before it runs out of power. Eventually, it should learn to avoid any detour and reach the charging station in the optimal number of steps.`
this.$lightbox.popup(lightText, ["next"]).then((r) => this.changeState("local"));
},
},
local: {
components: ["local", "navi", "score"],
navigation: {
"reset robot": () => machine.reset_machine(),
"continue": null,
},
onEnterState: function () {
this.navigation.continue = () => this.changeState("global");
var lightText = "But there is a problem! The robot cannot see the whole maze, it only knows where it is and in which direction it can move. Can you reach the charging station in those conditions? Use the arrows to move";
this.$lightbox.popup(lightText, ["next"]);
},
},
global: {
components: ["global", "sliders", "plot", "navi", "score"],
navigation: {
"run 1 episode!": () => machine.run(1),
"run 100 episodes!": () => machine.run(100),
"auto step!": () => machine.auto_step(),
"greedy step!": () => machine.greedy_step(),
"reset machine": () => machine.reset_machine(),
},
onEnterState: function () {
var lightText = `As a human, you keep track of where you are and how you got there without thinking, which helps you think about what actions you should take next to reach your destination. And you can also just look around! How can then the robot 'think' of the maze, to know which action is the best at every moment? And how can it learn that? It must somehow keep track of where it is, and remember how good or bad was each action at each place in the maze, try new things, and update it's "mental image" of what was a good decision and what not.
Reinforcement Learning uses the concept of a "Q-function", which keeps track of how "good" it expects it to be to take a specific action 'a' from a specific location 's'. This is written as Q(s, a). It also uses a "policy", which determines the best action to take in a given state, and is written as π(s). The robot must learn those functions while it navigates the maze. With each step, the functions are modified by a little bit, until eventually they give it the best strategy to solve the maze.`;
this.$lightbox.popup(lightText, ["continue"]);
},
}
};

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