Coordinated-Multi-Agent-Imitation-Learning
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This is an implementation of the paper "Coordinated Multi Agent Imitation Learning", or the Sloan version "Data-Driven Ghosting using Deep Imitation Learning" using Tensorflow
Would be good to see you after a while if you're still in Toronto. Here's my number 314 132 3417 (+1 to each digit)
these 2 paper all use soccer tracking dataset, so where Can I find the soccer tracking dataset?
Hi, thank you for sharing your work. Could you explain how can I start training and run a trained model? Thank you,
It may take too much time, but seems like MAP might produce a better result
> 2018-05-19 20:15:18,769 | INFO : Training with hyper parameters: {'use_model': 'dynamic_rnn_layer_norm', 'batch_size': 64, 'sequence_length': 50, 'overlap': 25, 'state_size': [128, 128], 'use_peepholes': None, 'input_dim': 179, 'dropout_rate': 0.6, 'learning_rate': 0.0001, 'n_epoch':...
https://arxiv.org/pdf/1606.00968.pdf http://www.yisongyue.com/publications/cvpr2016_online_smooth_long.pdf
For example, In game `0021500196`, event `2`, `'time_left': [705, 704, 685, 684]}`, `'event_str': ['miss', 'rebound', 'miss', 'rebound'],` and match these with the shot clock left and the court visualization, the...