diff --git a/README.md b/README.md index 4af82fe..5d6b84d 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ For each frame the bird stays alive, +0.1 score is given to him. For each wall h Try it yourself --------------- -You need python3 and pip for installing and running the code. +You need python3.5 and pip for installing and running the code. First, install dependencies (you might want to create a [virtualenv](https://virtualenv.pypa.io)): diff --git a/draw_chart.py b/draw_chart.py new file mode 100644 index 0000000..9f24304 --- /dev/null +++ b/draw_chart.py @@ -0,0 +1,39 @@ +import os +import plotly.plotly as py +import plotly.graph_objs as go +import plotly.io as pio + +def draw_chart(scatter_x, scatter_y, line_x, line_y): + marker_opts = dict( + name = 'Individual Reward', + x = scatter_x, + y = scatter_y, + mode = 'markers', + marker = { + 'size': 2 + } + ) + marker_trace = go.Scatter(**marker_opts) + line_opts = dict( + name = 'Mean Reward', + x = line_x, + y = line_y, + mode = 'lines' + ) + line_trace = go.Scatter(**line_opts) + + data = [marker_trace, line_trace] + + fig = go.Figure(data=data) + + log_layout = go.Layout( + yaxis = { + 'type': 'log', + 'autorange': True + } + ) + fig_log = go.Figure(data=data, layout=log_layout) + + pio.orca.config.executable = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'node_modules', 'orca', 'bin', 'orca.js') + pio.write_image(fig, 'fig.svg', width=1600, height=800) + pio.write_image(fig_log, 'fig-log.svg', width=1600, height=800) diff --git a/es.py b/es.py index 1002b5e..b4b88df 100644 --- a/es.py +++ b/es.py @@ -69,5 +69,5 @@ class EvolutionStrategy(): # np.dot(n.T, A) scales each noise's contribution to the update by how much reward it had received update = self.alpha / (self.noisep * self.sigma) * np.dot(n.T, A).T self.layers[i] = self.layers[i] + update - + return R diff --git a/fig-log.jpg b/fig-log.jpg new file mode 100644 index 0000000..34b59e7 Binary files /dev/null and b/fig-log.jpg differ diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000..c9ed7c1 --- /dev/null +++ b/package-lock.json @@ -0,0 +1,713 @@ +{ + "name": "flappy-es", + "version": "1.0.0", + "lockfileVersion": 1, + "requires": true, + "dependencies": { + "ajv": { + "version": "6.6.1", + "resolved": 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0000000..077f999 --- /dev/null +++ b/package.json @@ -0,0 +1,22 @@ +{ + "name": "flappy-es", + "version": "1.0.0", + "description": "Playing Flappy Bird using Evolution Strategies ==============================================", + "main": "index.js", + "scripts": { + "test": "echo \"Error: no test specified\" && exit 1" + }, + "repository": { + "type": "git", + "url": "git+https://github.com/mdibaiee/flappy-es.git" + }, + "author": "", + "license": "ISC", + "bugs": { + "url": "https://github.com/mdibaiee/flappy-es/issues" + }, + "homepage": "https://github.com/mdibaiee/flappy-es#readme", + "devDependencies": { + "orca": "^1.1.1" + } +} diff --git a/requirements b/requirements index c921e12..16c3e6b 100644 --- a/requirements +++ b/requirements @@ -1,31 +1,4 @@ -blinker==1.3 -chardet==2.3.0 -cloud-init==0.7.9 -command-not-found==0.3 -configobj==5.0.6 -cryptography==1.2.3 -idna==2.0 -Jinja2==2.8 -jsonpatch==1.10 -jsonpointer==1.9 -language-selector==0.1 -MarkupSafe==0.23 numpy==1.12.1 -oauthlib==1.0.3 -prettytable==0.7.2 -pyasn1==0.1.9 -pycurl==7.43.0 -pygobject==3.20.0 -PyJWT==1.3.0 -pyserial==3.0.1 -python-apt==1.1.0b1 -python-debian==0.1.27 -python-systemd==231 -PyYAML==3.11 -requests==2.9.1 -six==1.10.0 -ssh-import-id==5.5 -ufw==0.35 -unattended-upgrades==0.1 -urllib3==1.13.1 -virtualenv==15.0.1 +plotly==3.4.0 +psutil==5.4.6 +PyGObject==3.30.4 diff --git a/train.py b/train.py index 36379e4..3649941 100644 --- a/train.py +++ b/train.py @@ -7,6 +7,7 @@ from gi.repository import Gtk, GLib, Gdk from datetime import datetime from os import path import os +from draw_chart import draw_chart es = EvolutionStrategy(fn=play, noisep=50, sigma=0.1, alpha=0.001, layer_sizes=[[4, 500], [500, 1]], input_size=4) load = path.join(path.dirname(__file__), 'load.npy') @@ -14,13 +15,15 @@ load = path.join(path.dirname(__file__), 'load.npy') np.random.seed(0) # if load.npy exists, load the parameters from it -if path.exists(load): +if path.exists(load) and not os.environ.get('SKIP_LOAD'): es.layers = np.load(load) # show the game every n iterations -SHOW_EVERY = 100 +SHOW_EVERY = int(os.environ.get('SHOW_EVERY', 100)) # save the parameters every n iterations -SAVE_EVERY = 100 +SAVE_EVERY = int(os.environ.get('SAVE_EVERY', 100)) +# number of steps +STEPS = int(os.environ.get('STEPS', 10000)) # an id for saving the parameters in a folder run_id = str(datetime.now()) @@ -45,9 +48,22 @@ def timeout_kill(win, game): return True -for i in range(10000): +reward_scatter_x = [] +reward_scatter_y = [] + +reward_line_x = list(range(STEPS)) +reward_line_y = [] + +for i in range(STEPS): print("{}: ".format(i), end='') - es.train() + rewards = es.train() + m = np.mean(rewards) + + reward_line_y.append(m) + + for r in rewards: + reward_scatter_x.append(i) + reward_scatter_y.append(r) if SHOW_EVERY and i % SHOW_EVERY == 0: play(es.forward, step=step) @@ -60,4 +76,4 @@ for i in range(10000): if i % SAVE_EVERY == 0: p = path.join(path.dirname(__file__), 'saves', run_id, 'save-{}'.format(i)) np.save(p, es.layers) - + draw_chart(reward_scatter_x, reward_scatter_y, reward_line_x, reward_line_y)