done at gios

Author: pascalwhoop

src/chaps/introduction.tex

@@ -1,3 +1,49 @@
 TODO Intro comes at the end
 
-overall motivation, previous research, 
+% intro structuring basing on style from https://explorationsofstyle.com/2013/01/22/introductions/
+%Intro short:
+% - global warming, lots of problems
+% - reinvent the energy grid, lots of changes to the structure
+%   - very difficult to construct such a highly complex, globally spanning, must-never-fail system
+% - recent developments of of A.I. and machine learning
+% - combine the two
+
+%Intro long
+% - energy grids of the future background research (PTac)
+%     - key components of such an intelligent agent (prediction, actions --> \ac {SL} and \ac {RL} )
+% - research in \ac {SL} and \ac {RL} has seen huge improvements in recent years, thanks to \ac {NN} 
+% - agents/brokers in the field of PTac haven't been seeing much of these improvements
+% - also an issue of "adopting what has been learned by previous agents (transfer learning issues)"
+% - 
+% - 
+%TODO reiterate over the research question from my proposal. Is it still applicable?
+
+%-------------------------------------------------------------------------------  
+%\emph{Can \ac{RL} agents learn from other agents in the environment? If so, how? Can mutual learning and imitation
+%allow for boosted performance of reinforcement algorithms within a competitive simulation environment?}
+%------------------------------------------------------------------------------- 
+
+Global warming is a key challenge of the near and medium future. Without proper action, entire continents will see
+%TODO END
+
+Global warming, if not combated, will change the face of the planet. Billions will be impacted, entire coastlines will
+be changed and cities all over the global will have to either be retrofitted to handle sub-sea level positioning or
+abandoned and relocated. (global warming report)
+
+
+One key component to avoid such disastrous effects is the reinvention of the energy systems of the world. While
+appliances on an individual level need to become ever more efficient, globally it is necessary to shift the
+transportation sector towards renewable energy sources.
+Solar and wind
+are required. But The future of energy is difficult (--> MISQ paper argumentation line)
+
+Smart grids need decentralized intelligence where appliance level evaluation of the grid status impacts how energy is
+consumed. When such intelligence shifting is happening towards the \emph{edge} of the grid, it can be intelligent to
+introduce intermediate broker entities that mediate between the two extremes, the end-consumers and the wholesale
+market.
+
+At the same time, current developments in AI and machine learning allow for highly sophisticated learning machines that
+can help manage complex tasks and systems. (citing some sexy AI papers)
+
+Bringing these two developments together, it is intuitive to apply some of the recently developed technologies of 
+\ac {AI} research to solve the coordination issues of contemporary, frankly crude energy networks. 

thesis.vim

@@ -1,3 +1,5 @@
+ab ---      %-------------------------------------------------------------------------------
+ab ===      %===============================================================================
 ab RL       \ac {RL}
 ab GRPC     \ac {GRPC}
 ab UL       \ac {UL}