The goal of the Angry Birds AI competition is to build an intelligent agent which can complete the levels of the game better than human players. This task is very challenging, because humans have a good prediction about the physic world, while for computers it is hard to reason about an unknown environment. In this paper we describe our DualHEX AI agent, which is based on the AngryHEX agent of participants of the Angry Birds competition 2013. Our agent models the knowledge of the game by means of Answer Set Programming. In this project we improved the AngryHEX approach by extending the knowledge base of the domain. Our DualHEX agent plans a shot taking into consideration the current and the next bird. It compares the damage probability of both birds to discard targets that suits more the next bird features.
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