This python code is for paper ''Thompson Sampling for a Fatigue-aware Online Recommendation System''. Please find details on https://arxiv.org/abs/1901.07734
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Based_define_function.py: This code provide the basic function used in the paper, i.e. calculate the order of messages, the users feedback, the total payoff, etc.
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Thompsonbasedpy.py: This code provides function thompson_base that we implement algorithm 1.
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TSgaussian.py: This code provides function TSgaussian_base that we implement algorithm 1.
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UCBV.py: This code provides function ucbv that we implement algorithm 3.
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ucbbasedpy.py: This code provides function ucb_base that we implement algorithm in Cao and Sun (2019).
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experiment.py: This code calls the function from other py file. The current experiment.py file is that we call algorithm 2 to do 10 times experiments using different R alpha and beta. We record the result in txt file and pickle down in result file.
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testfile.py: This code plots the chart of the result of each algorithm in the result file. The current testfile.py file is that we plot the result chart of algorithm 1 when u is generated from [0, 0.5].