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# Contributing
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This project welcomes contributions and suggestions. Most contributions require you to
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agree to a Contributor License Agreement (CLA) declaring that you have the right to,
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and actually do, grant us the rights to use your contribution. For details, visit
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https://cla.microsoft.com.
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When you submit a pull request, a CLA-bot will automatically determine whether you need
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to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the
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instructions provided by the bot. You will only need to do this once across all repositories using our CLA.
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
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or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
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2
LICENSE
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LICENSE
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MIT License
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MIT License
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LOGARITHMIC REINFORCEMENT LEARNING
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Copyright (c) Microsoft Corporation.
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Copyright (c) Microsoft Corporation.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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Permission is hereby granted, free of charge, to any person obtaining a copy
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## OSS License Notice
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The files in the `log_dqn_experiments/log_dqn
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` folder are mostly derived from [Dopamine](https://github.com/google/dopamine). Please see the original license [here](https://github.com/google/dopamine/blob/master/LICENSE).
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@ -4,7 +4,9 @@ This repository hosts sample code for the NeurIPS 2019 paper: [van Seijen, Fatem
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We provide code for the linear experiments of the paper as well as the deep RL Atari 2600 examples (LogDQN).
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We provide code for the linear experiments of the paper as well as the deep RL Atari 2600 examples (LogDQN).
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## For the license, please see [LICENSE](https://github.com/microsoft/logrl/blob/master/LICENSE).
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## [LICENSE](https://github.com/microsoft/logrl/blob/master/LICENSE)
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## [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct)
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The code for LogDQN has been developed by [Arash Tavakoli](https://atavakol.github.io/) and the code for the linear experiments has been developed by [Harm van Seijen](mailto:Harm.vanSeijen@microsoft.com).
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The code for LogDQN has been developed by [Arash Tavakoli](https://atavakol.github.io/) and the code for the linear experiments has been developed by [Harm van Seijen](mailto:Harm.vanSeijen@microsoft.com).
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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import numpy as np
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import numpy as np
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class Agent(object):
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class Agent(object):
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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import numpy as np
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import numpy as np
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import math
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import math
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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import numpy as np
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import numpy as np
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import json
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import json
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import time
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import time
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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import numpy as np
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import numpy as np
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import math
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import math
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import json
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import json
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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name = "log_dqn"
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name = "log_dqn"
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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# This file is derived from Dopamine with the following original copyright note:
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# Copyright 2018 The Dopamine Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""The standard DQN replay memory modified to support float64 rewards.
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"""The standard DQN replay memory modified to support float64 rewards.
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This script modifies the Dopamine's implementation of an out-of-graph
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This script modifies the Dopamine's implementation of an out-of-graph
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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# This file is partially derived from Dopamine with the following original copyright note:
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# Copyright 2018 The Dopamine Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Compact implementation of a LogDQN agent.
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"""Compact implementation of a LogDQN agent.
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Details in "Using a Logarithmic Mapping to Enable Lower Discount Factors
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Details in "Using a Logarithmic Mapping to Enable Lower Discount Factors
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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# This file is partially derived from Dopamine with the following original copyright note:
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# Copyright 2018 The Dopamine Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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r"""The entry point for running an agent on an Atari 2600 domain.
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r"""The entry point for running an agent on an Atari 2600 domain.
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This script modifies Dopamine's `train.py` to support LogDQN.
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This script modifies Dopamine's `train.py` to support LogDQN.
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'''
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Copyright (c) Microsoft Corporation.
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Licensed under the MIT license.
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'''
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import codecs
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import codecs
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from os import path
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from os import path
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from setuptools import find_packages
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from setuptools import find_packages
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