Hi..!!
After going through ticket reports listed in http://trac.sagemath.org/report/75?sort=component&asc=1&page=2 , I have put some of the games in the form of code (I am still working on the structure of the code and will soon update them) : https://github.com/ankuromar296/game_theory These are very basic implementation and needs a lot of modification to include more number of players. With the time given, more functionality will be added to the module. I have put up my proposal on melange site and want suggestions to improve it further. For the research paper on cognitive radio networks, I coded the game theoretic behavior myself using MATLAB, but the extent to which it could be implemented was very limited. I wish to increase this extent by adding more games to the existing module of game theory in sage. Given a situation if the variables of influence are known then the program itself can provide one or more nash equilibrium (test for degeneracy) according to the payoffs, which will be very useful in situations where there are a large number of players and a large number of strategies that each player can adopt. At present, the modules in sage include very few game models with limited players. I wish to increase the functionality of the tool to include more players and more game models as mentioned above. Since, gambit already has a decent code base of game theory, with every game in its complete form, main focus will be to integrate them with gambit as well. Focus will also be on enhancing the user interface of gambit to accommodate the newly coded games. *Details :* Designing each game will have these particular individual tasks : 1. Writing down all the possible strategies and payoff related to each strategy for a player. 2. Providing input functionality. 3. Writing test function to check whether there is an ambiguity in the input. 4. Providing the optimum strategy and nash equilibrium for a given set of strategies adopted by a group of players. 5. Functionality to add or remove strategies in a given game. 6. Test for degeneracy 7. Writing testable examples to avoid bugs. 8. Integration with gambit 9. Transferring the results into LaTex. My aim will be to complete two games at a time, so that by the time the summer of code ends, I have a set of games in their complete form which can be combined with the existing source. Keeping the above mentioned tasks as the primary objective, secondary objective will be to include multi-player functionality to each game. I will be highly grateful if people from the community can give some valuable suggestions to improve my proposal since the deadline for submission is nearby. Thank You, *Ankur Omar* On Tuesday, March 17, 2015 at 6:17:59 PM UTC+5:30, Ankur Omar wrote: > > Hi! > > I am a third year undergraduate from Birla Institute of Technology and > Science, Pilani - Goa Campus. I feel I am a bit late, but I am really > interested in pursuing this project for this years Google Summer of Code. I > have published a single authored research paper on Cognitive Radio Networks > using *Game Theory *titled " Cache Node Determination, Allocation and > Distribution in Cognitive Networks Using Game Theory" " > http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7020890 " in IEEE > sponsored ATNAC Conference held in Melbourne, Australia, last november. I > have a very deep interest in Game Theory and have been working on > implementing it in cognitive radio networks and Brain functionality. I > strongly feel that I will be able to contribute very well for this project. > I will be highly glad if you can assist me further to get started with this > project. > > Thank You. > > Regards > Ankur Omar > B.E.(Hons.) Electronics and Instrumentation > -- You received this message because you are subscribed to the Google Groups "sage-gsoc" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/sage-gsoc. For more options, visit https://groups.google.com/d/optout.
