Candidate topics for a Research/Programming Project

Content Based Recommendation System to Events

Choose which bar, show, theater, play or any sort of event, go or do not go can be a big issue for people who live in a big city with a lot of options, or even to people who are visiting a new city. There are some apps, as Foursquare, that could help in this situations, but none of them gives personal recommendation and none of them are based in events. This project would be the creation of a recommendation system to events, where the user could see their prefer kind of events, and a guess about how they would rate those events. In this way, the user would save time, instead of look at all events in the city to choose which one is the best, the user could simply see the top ten events for him. The system would provides personalized recommendation by matching user’s interests with description and attributes of this events. For example, the place, actors, artists, theme, day of week, time kind of music and etc. Moreover, the system would obtain the user’s interests using their likes or dislikes in previous events, their friends interests or even a initial interview. The machine learning would be an essential part of the system, for example, a decision tree could be used to learn a model that smartly chooses minimum set of question while learning user's preference in the initial interview. Moreover, for the recommendation of the event, some standard techniques of machine learning could be used, such as, logistic regression, support vector machines, decision tree or other. Considering the natural interaction required to this system, it should be web based. 

Real-Time Learning with Dynamic Obstacles Applied in A PacMan

Real time learning algorithms are commonly used in situations that the agent has to interleaves planning and acting to have a quick answer on a path finding problem. Also, some of those algorithms include obstacles in their analysis, obstacles that can be dynamic or not. It can be used in many different situations, for example a flying drone or a robust robot motion planning in dynamic environments. The project to the course could be the application of some of these algorithms, such as, LSS-LRTA* or neural networks, to a PacMan game.

Articles that can help

http://rvsn.csail.mit.edu/location/Minkov_collaborative_recommendation.pdf http://www.aaai.org/ocs/index.php/SOCS/SOCS12/paper/viewFile/5412/5174 http://www.gamesitb.com/nnpathgraham.pdf
http://www.gamesitb.com/pathgraham.pdf

Other Ideas

Smart Othello - Reversi Game
Traffic Tweet Classifier