@inproceedings{db63ec55e7eb487baf758240edb37292,
title = "Using restart heuristics to improve agent performance in Angry Birds",
abstract = "Over the past few years the Angry Birds AI competition has been held in an attempt to develop intelligent agents that can successfully and efficiently solve levels for the video game Angry Birds. Many different agents and strategies have been developed to solve the complex and challenging physical reasoning problems associated with such a game. However none of these agents attempt one of the key strategies which humans employ to solve Angry Birds levels, which is restarting levels. Restarting is important in Angry Birds because sometimes the level is no longer solvable or some given shot made has little to no benefit towards the ultimate goal of the game. This paper proposes a framework and experimental evaluation for when to restart levels in Angry Birds. We demonstrate that restarting is a viable strategy to improve agent performance in many cases.",
keywords = "Angry Birds, Heuristics, Qualitative Spatial Reasoning, Restarts, Video Games",
author = "Tommy Liu and Jochen Renz and Peng Zhang and Matthew Stephenson",
year = "2019",
month = aug,
doi = "10.1109/CIG.2019.8848039",
language = "English",
isbn = "9781728118857",
series = "IEEE Conference on Computatonal Intelligence and Games, CIG",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IEEE Conference on Games 2019, CoG 2019",
note = "2019 IEEE Conference on Games, CoG 2019 ; Conference date: 20-08-2019 Through 23-08-2019",
}