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## Eidesstattliche Erklärung | ||
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Hiermit versichere ich an Eides statt, dass ich die vorliegende Arbeit selbst- ständig und ohne die Benutzung anderer | ||
als der angegebenen Hilfsmittel angefertigt habe. Alle Stellen, die wörtlich oder sinngemäß aus veröffentlichten und | ||
nicht veröffentlichten Schriften entnommen wurden, sind als solche kenntlich gemacht. Die Arbeit ist in gleicher oder | ||
ähnlicher Form oder auszugsweise im Rahmen einer anderen Prüfung noch nicht vorgelegt worden. Ich versichere, dass die | ||
eingereichte elektronische Fassung der eingereichten Druckfassung vollständig entspricht. | ||
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\chapter{Preface} | ||
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This thesis was planned and discussed in the winter of 17/18. On February 1st, the work phase of six months started. | ||
Within these six months, I discovered many previously unknown or unforeseen complexities. These include the | ||
communication technologies developed to permit a complete python based broker and a large variety of API approaches | ||
within the RL agent libraries currently available. While I have invested a significant amount of effort into the | ||
development of the required components, I always intended to build something that may be reused in the future instead of | ||
being discarded after my thesis was graded. This lead me to the decision of implementing a best practice based | ||
communication instead of a quick minimal approach and led me to try and write my python code in a way that will let | ||
future broker developers reuse it as a framework for their broker implementations. | ||
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As of July, I was not able to complete my research question and reach the intended target of evaluating a variety of | ||
neural network architectures that let a RL learn from other agents in its environment. Because of university | ||
regulations, changing a thesis title is not permitted. And while my research question was not answered, I believe I have | ||
contributed something valuable for the PowerTAC community. With my implementation, current state-of-the-art neural | ||
network algorithms and especially reinforcement agent implementations can be used to act in the PowerTAC competition. | ||
While I was not able to complete this in time and offer valubale, testable results, it is nonetheless now possible to | ||
work on a broker and to focus on the core problems of RL learning problems: Environment observation filtering, NN input | ||
preprocessing, reward function definition, NN architecture experimentation etc. With the created Docker images, | ||
developers are quickly able to start a competition with multiple brokers and future participants may be encouraged to | ||
adopt the Docker based distribution of their agents to include more advanced technologies in their broker | ||
implementations without placing a burden on others to manage these dependencies. | ||
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When reading the thesis, please be aware that the title does not match the contents as one would expect. If I had more | ||
time to work on this project, by the time I handed in my thesis I was at the point where I could have started developing | ||
and experimenting with a number of RL agent implementations and to make the project complete. Unfortunately, I fell | ||
into the same trap that many software engineers and entire project teams fall into: Underestimating the complexity of | ||
the project which leads to either loss in quality, time overruns or budget overruns. I recognize this mistake but I | ||
cannot fix it today. I hope the thesis is still valuable to anyone who reads it and maybe the next graduate theses will | ||
continue where I left off. |
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