2048-Framework

Framework for 2048 & 2048-Like Games (C++ 11)

Basic Usage

To make the sample program:

make # see makefile for details

To run the sample program:

./2048 # by default the program runs 1000 games

To specify the total games to run:

./2048 --total=100000

To display the statistics every 1000 episodes:

./2048 --total=100000 --block=1000 --limit=1000

To specify the total games to run, and seed the environment:

./2048 --total=100000 --place="seed=12345" # need to inherit from random_agent

To save the statistics result to a file:

./2048 --save=stats.txt

To load and review the statistics result from a file:

./2048 --load=stats.txt

Advanced Usage

To initialize the network, train the network for 100000 games, and save the weights to a file:

weights_size="65536,65536,65536,65536,65536,65536,65536,65536" # 8x4-tuple
./2048 --total=100000 --block=1000 --limit=1000 --slide="init=$weights_size save=weights.bin" # need to inherit from weight_agent

To load the weights from a file, train the network for 100000 games, and save the weights:

./2048 --total=100000 --block=1000 --limit=1000 --slide="load=weights.bin save=weights.bin" # need to inherit from weight_agent

To train the network for 1000 games, with a specific learning rate:

weights_size="65536,65536,65536,65536,65536,65536,65536,65536" # 8x4-tuple
./2048 --total=1000 --slide="init=$weights_size alpha=0.0025" # need to inherit from weight_agent

To load the weights from a file, test the network for 1000 games, and save the statistics:

./2048 --total=1000 --slide="load=weights.bin alpha=0" --save="stats.txt" # need to inherit from weight_agent

To perform a long training with periodic evaluations and network snapshots:

weights_size="65536,65536,65536,65536,65536,65536,65536,65536" # 8x4-tuple
./2048 --total=0 --slide="init=$weights_size save=weights.bin" # generate a clean network
for i in {1..100}; do
	./2048 --total=100000 --block=1000 --limit=1000 --slide="load=weights.bin save=weights.bin alpha=0.0025" | tee -a train.log
	./2048 --total=1000 --slide="load=weights.bin alpha=0" --save="stats.txt"
	tar zcvf weights.$(date +%Y%m%d-%H%M%S).tar.gz weights.bin train.log stats.txt
done

Author

Hung Guei, Computer Games and Intelligence (CGI) Lab, NYCU, Taiwan