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sesiuni:basics-of-reinforcement-learning [2018/08/09 20:41] amacovei |
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== Basics of Reinforcement Learning == | == Basics of Reinforcement Learning == | ||
+ | |||
+ | Mentor: Ioana Veronica Chelu\\ | ||
+ | [[ioana.chelu28@gmail.com|ioana.chelu28@gmail.com]] | ||
== Overview == | == Overview == | ||
- | Starting from the idea of learning as the basis for intelligence, reinforcement learning (RL) has been proposed as the adaptive learning-based algorithm for decision making in animals emphasizing that the elements we encounter in this framework have empirical evidence accumulated from neuroscience studies. | + | Starting from the idea of learning as the basis for intelligence, reinforcement learning (RL) has been proposed as the adaptive learning-based algorithm for decision making in animals emphasizing that the elements we encounter in this framework have empirical evidence accumulated from neuroscience studies.\\ \\ |
This workshop is concerned with setting RL in the framework of Markov Decision Processes, learning how to obtain goal-directed behavior of an agent by means of pure interaction with an environment. It is mixed with practical examples of learning with it. | This workshop is concerned with setting RL in the framework of Markov Decision Processes, learning how to obtain goal-directed behavior of an agent by means of pure interaction with an environment. It is mixed with practical examples of learning with it. | ||
It will also briefly overview some of the recent success stories concerning RL and some research challenges and frontiers in this field of research. | It will also briefly overview some of the recent success stories concerning RL and some research challenges and frontiers in this field of research. | ||
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- Interact with a deep learning framework for function approximation and apply this to the same task of learning from trial and error behavior. | - Interact with a deep learning framework for function approximation and apply this to the same task of learning from trial and error behavior. | ||
- | == Tutorials == | + | == Format and Curriculum == |
+ | The workshop will be held on 28, 30 and 31 August, at 9:00 AM. | ||
- | Python - basic introduction http://cs231n.github.io/python-numpy-tutorial/ \\ | ||
- | Environment setup for the practical session - download ipython notebooks and place them in your Google Drive, use colab to view or edit them. \\ | + | == Tutorials == |
+ | Environment setup for the practical session - download ipython notebooks and place them in your Google Drive, use colab to view or edit them.\\ | ||
+ | |||
+ | Python - basic introduction [[http://cs231n.github.io/python-numpy-tutorial/|Click]] \\ | ||
+ | Intro colab: | ||
+ | [[https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Colab.ipynb|Click]] \\ | ||
+ | Intro numpy: | ||
+ | [[https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Numpy.ipynb|Click]] \\ | ||
+ | Intro matplotlib: | ||
+ | [[https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Plotting.ipynb|Click]] (optional dar recomandat)\\ | ||
+ | Intro tensorflow and sonnet: | ||
+ | [[https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Tensorflow_and_Sonnet.ipynb|Click]]\\ | ||
+ | |||
+ | Special thanks to the organizers, speakers and lab assistants of the TMLSS - Transylvanian Machine Learning Summer School (https://tmlss.ro/) for the content of the labs presented during the workshops.\\ | ||
+ | == Registration == | ||
- | Ipython notebooks:\\ | + | Click [[https://docs.google.com/forms/d/e/1FAIpQLSfHr7HkhcZLNFhnrpixsbI7cwiaAKKssnLMI_i0__f945PRFw/viewform|here]]. |
- | Intro colab: https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Colab.ipynb \\ | + | |
- | Intro numpy: https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Numpy.ipynb \\ | + | |
- | Intro matplotlib: https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Plotting.ipynb (optional dar recomandat) \\ | + | |
- | Intro tensorflow and sonnet: https://github.com/ioanachelu/PracticalSessions/blob/master/introductory/Intro_Tensorflow_and_Sonnet.ipynb (optional dar recomandat) \\ | + |