Events Calendar

Thesis Proposal (Sasha Volokh)

Thesis Proposal Committee Members:
William G.J. Halfond (Chair)
Nenad Medvidovic
Andrew Nealen
Mukund Raghothaman
Chao Wang    
 
Abstract:
Modern computer games often release with significant bugs, causing consumer dissatisfaction and a loss of business and reputation for the companies involved. Testing is a key mechanism by which these issues can be caught and addressed during development. A key requirement for thorough manual and automated testing of games is knowledge of the possible player actions and their associated device inputs. In this thesis I propose novel program analysis techniques to inform both automated testing agents and human testers of the possible game actions. First, I propose a symbolic analysis technique that automatically analyzes the user input handling logic present in games to determine a discrete action space, along with the conditions under which the actions are valid, and the device inputs associated with each action. I then demonstrate how this technique can be adapted to enable effective performance in agents that automatically explore game functionalities. Next, I propose adapting this technique for game playing reinforcement learning agents. Finally, I propose methods to automatically generate in-game instructions for human testers based on the outcome of the action analysis.

Location: Charles Lee Powell Hall (PHE) - 325

Audiences: Everyone Is Invited

Contact: CS Events