@PHDTHESIS{cardamone2012phd,

  author = {Luigi Cardamone},
  title = {Evolutionary Learning and Search-Based Content Generation in Computer
	Games},
  school = {Politecnico di Milano},
  year = {2012},
  keywords = {search-based, content generation, evolutionary learning, on-line learning,
	transfer learning, genetic algorithms, neural networks, NEAT},
  owner = {luigi},
  timestamp = {2012.03.12}

}

@MASTERSTHESIS{cardamone2008masterthesis,

  author = {Luigi Cardamone},
  title = {On-line and Off-line Learning of Driving Tasks for The Open Racing
	Car Simulator (TORCS) Using Neuroevolution},
  school = {Politecnico di Milano},
  year = {2008},
  timestamp = {2009.06.06}

}

@MASTERSTHESIS{cardamone2006thesis,

  author = {Luigi Cardamone},
  title = {Progettazione e implementazione di un robot mobile dotato di un sistema
	di visione laser per la percezione della profonditÓ},
  school = {Politecnico di Milano},
  year = {2006},
  timestamp = {2009.06.06}

}

@INPROCEEDINGS{cardamone2011transfer,

  author = {Cardamone, Luigi and Caiazzo, Antonio and Loiacono, Daniele and Lanzi,
	Pier Luca},
  title = {Transfer of driving behaviors across different racing games},
  booktitle = {Computational Intelligence and Games (CIG), 2011 IEEE Conference
	on},
  year = {2011},
  pages = {227 -234},
  month = {31 2011-sept. 3},
  doi = {10.1109/CIG.2011.6032011},
  owner = {luigi},
  timestamp = {2011.10.07}

}

@INPROCEEDINGS{cardamone09on-line,

  author = {Cardamone, L. and Loiacono, D. and Lanzi, P.L.},
  title = {On-line neuroevolution applied to The Open Racing Car Simulator},
  booktitle = {Evolutionary Computation, 2009. CEC '09. IEEE Congress on},
  year = {2009},
  pages = {2622-2629},
  month = {May},
  abstract = {The application of on-line learning techniques to modern computer
	games is a promising research direction. In fact, they can be used
	to improve the game experience and to achieve a true adaptive game
	AI. So far, several works proved that neuroevolution techniques can
	be successfully applied to modern computer games but they are usually
	restricted to offline learning scenarios. In on-line learning problems
	the main challenge is to find a good trade-off between the exploration,
	i.e., the search for better solutions, and the exploitation of the
	best solution discovered so far. In this paper we propose an on-line
	neuroevolution approach to evolve non-player characters in The Open
	Car Racing Simulator (TORCS), a state-of-the-art open source car
	racing simulator. We tested our approach on two on-line learning
	problems: (i) on-line evolution of a fast controller from scratch
	and (ii) optimization of an existing controller for a new track.
	Our results show that on-line neuroevolution can effectively improve
	the performance achieved during the learning process.},
  doi = {10.1109/CEC.2009.4983271},
  keywords = {Internet, computer games, learning (artificial intelligence), neural
	net architectureThe Open Car Racing Simulator, computer games, nonplayer
	characters, offline learning scenario, online evolution, online learning
	problem, online learning technique, online neuroevolution, open racing
	car simulator, open source car racing simulator, true adaptive game
	AI},
  timestamp = {2009.09.14}

}

@INPROCEEDINGS{cardamone2011interactive,

  author = {Cardamone, Luigi and Loiacono, Daniele and Lanzi, Pier Luca},
  title = {Interactive evolution for the procedural generation of tracks in
	a high-end racing game},
  booktitle = {Proceedings of the 13th annual conference on Genetic and evolutionary
	computation},
  year = {2011},
  series = {GECCO '11},
  pages = {395--402},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {2001631},
  doi = {http://doi.acm.org/10.1145/2001576.2001631},
  isbn = {978-1-4503-0557-0},
  keywords = {interactive genetic algorithms, procedural content generation, racing
	games},
  location = {Dublin, Ireland},
  numpages = {8},
  owner = {luigi},
  timestamp = {2011.09.12},
  url = {http://doi.acm.org/10.1145/2001576.2001631}

}

@INPROCEEDINGS{cardamone10cooperative,

  author = {Cardamone, Luigi and Loiacono, Daniele and Lanzi, Pier Luca},
  title = {Applying cooperative coevolution to compete in the 2009 TORCS Endurance
	World Championship},
  year = {2010},
  pages = {1 -8},
  month = {jul.},
  doi = {10.1109/CEC.2010.5586041},
  journal = {Evolutionary Computation (CEC), 2010 IEEE Congress on},
  owner = {luigi},
  timestamp = {2010.10.06}

}

@ARTICLE{cardamone10learning,

  author = {Cardamone, L. and Loiacono, D. and Lanzi, P. L.},
  title = {Learning to Drive in the Open Racing Car Simulator Using Online Neuroevolution},
  journal = {Computational Intelligence and AI in Games, IEEE Transactions on},
  year = {2010},
  volume = {2},
  pages = {176 -190},
  number = {3},
  month = {sep.},
  doi = {10.1109/TCIAIG.2010.2052102},
  issn = {1943-068X},
  owner = {luigi},
  timestamp = {2010.10.06}

}

@INPROCEEDINGS{cardamone09evolving,

  author = {Cardamone, Luigi and Loiacono, Daniele and Lanzi, Pier Luca},
  title = {Evolving competitive car controllers for racing games with neuroevolution},
  booktitle = {GECCO '09: Proceedings of the 11th Annual conference on Genetic and
	evolutionary computation},
  year = {2009},
  pages = {1179--1186},
  address = {New York, NY, USA},
  publisher = {ACM},
  doi = {http://doi.acm.org/10.1145/1569901.1570060},
  isbn = {978-1-60558-325-9},
  location = {Montreal, Qu\'{e}bec, Canada},
  timestamp = {2009.09.14}

}

@INPROCEEDINGS{cardamone09learning,

  author = {Cardamone, Luigi and Loiacono, Daniele and Lanzi, Pier Luca},
  title = {Learning drivers for TORCS through imitation using supervised methods},
  booktitle = {Computational Intelligence and Games, 2009. CIG 2009. IEEE Symposium
	on},
  year = {2009},
  pages = {148-155},
  month = {Sept.},
  doi = {10.1109/CIG.2009.5286480},
  owner = {luigi},
  timestamp = {2009.10.16}

}

@INPROCEEDINGS{cardamone10racingline,

  author = {Cardamone, Luigi and Loiacono, Daniele and Lanzi, Pier Luca and Bardelli,
	Alessandro Pietro},
  title = {Searching for the optimal racing line using genetic algorithms},
  year = {2010},
  pages = {388 -394},
  month = {aug.},
  doi = {10.1109/ITW.2010.5593330},
  journal = {Computational Intelligence and Games (CIG), 2010 IEEE Symposium on},
  owner = {luigi},
  timestamp = {2010.10.27}

}

@INPROCEEDINGS{Cardamone:2011:DSoPIuGP,

  author = {Luigi Cardamone and Andrea Mocci and Carlo Ghezzi},
  title = {Dynamic Synthesis of Program Invariants using Genetic Programming},
  booktitle = {Proceedings of the 2011 IEEE Congress on Evolutionary Computation},
  year = {2011},
  editor = {Alice E. Smith},
  pages = {617--624},
  address = {New Orleans, USA},
  month = {5-8 June},
  organization = {IEEE Computational Intelligence Society},
  publisher = {IEEE Press},
  abstract = {In the field of software engineering, invariant detection techniques
	have been proposed to overcome the problem of software behavior comprehension.
	If the code of a program is available, combining symbolic and concrete
	execution has been shown to provide an effective method to derive
	logic formulae that describe a program's behavior. However, symbolic
	execution does not work very well with loops, and thus such methods
	are not able to derive useful descriptions of programs containing
	loops. In this paper, we present a preliminary approach that aims
	to integrate genetic programming to synthesize a logic formula that
	describes the behavior of a loop. Such formula could be integrated
	in a symbolic execution based approach for invariant detection to
	synthesize a complex program behavior. We present a specific representation
	of formulae that works well with loops manipulating arrays. The technique
	has been validated with a set of relevant examples with increasing
	complexity. The preliminary results are promising and show the feasibility
	of our approach.},
  isbn = {0-7803-8515-2},
  keywords = {Genetic programming},
  notes = {CEC2011 sponsored by the IEEE Computational Intelligence Society,
	and previously sponsored by the EPS and the IET. },
  owner = {luigi},
  timestamp = {2011.06.23}

}

@INPROCEEDINGS{cardamone2011evolving,

  author = {Cardamone, Luigi and Yannakakis, Georgios N. and Togelius, Julian
	and Lanzi, Pier Luca},
  title = {Evolving interesting maps for a first person shooter},
  booktitle = {Proceedings of the 2011 international conference on Applications
	of evolutionary computation - Volume Part I},
  year = {2011},
  series = {EvoApplications'11},
  pages = {63--72},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  acmid = {2008411},
  isbn = {978-3-642-20524-8},
  keywords = {evolutionary algorithms, first-person shooters, games, player experience,
	procedural content generation, search-based},
  location = {Torino, Italy},
  numpages = {10},
  owner = {luigi},
  timestamp = {2011.09.12},
  url = {http://dl.acm.org/citation.cfm?id=2008402.2008411}

}

@INPROCEEDINGS{galli2011cheating,

  author = {Galli, Luca and Loiacono, Daniele and Cardamone, Luigi and Lanzi,
	Pier Luca},
  title = {A cheating detection framework for Unreal Tournament III: A machine
	learning approach},
  booktitle = {Computational Intelligence and Games (CIG), 2011 IEEE Conference
	on},
  year = {2011},
  pages = {266 -272},
  month = {31 2011-sept. 3},
  doi = {10.1109/CIG.2011.6032016},
  owner = {luigi},
  timestamp = {2011.10.07}

}

@ARTICLE{loiacono2011automatic,

  author = {Loiacono, D. and Cardamone, L. and Lanzi, P. L.},
  title = {Automatic Track Generation for High-End Racing Games Using Evolutionary
	Computation},
  journal = {Computational Intelligence and AI in Games, IEEE Transactions on},
  year = {2011},
  volume = {3},
  pages = {245 -259},
  number = {3},
  month = {sept. },
  doi = {10.1109/TCIAIG.2011.2163692},
  issn = {1943-068X},
  owner = {luigi},
  timestamp = {2011.09.14}

}

@ARTICLE{loiacono10scr,

  author = {Loiacono, D. and Lanzi, P.L. and Togelius, J. and Onieva, E. and
	Pelta, D.A. and Butz, M.V. and Lönneker, T.D. and Cardamone, L.
	and Perez, D. and Sáez, Y. and Preuss, M. and Quadflieg, J.},
  title = {The 2009 Simulated Car Racing Championship},
  journal = {Computational Intelligence and AI in Games, IEEE Transactions on},
  year = {2010},
  volume = {2},
  pages = {131 -147},
  number = {2},
  month = {jun.},
  doi = {10.1109/TCIAIG.2010.2050590},
  issn = {1943-068X},
  keywords = {2009 ACM Genetic and Evolutionary Computation Conference;2009 IEEE
	Congress on Evolutionary Computation;2009 IEEE Symposium on Computational
	Intelligence and Games;2009 Simulated Car Racing Championship;competition
	regulations;high-performing car racing controllers;scientific competitions;evolutionary
	computation;learning (artificial intelligence);sport;},
  owner = {luigi},
  timestamp = {2010.09.18}

}

@INPROCEEDINGS{loiacono10overtake,

  author = {Loiacono, Daniele and Prete, Alessandro and Lanzi, Pier Luca and
	Cardamone, Luigi},
  title = {Learning to overtake in TORCS using simple reinforcement learning},
  year = {2010},
  pages = {1 -8},
  month = {jul.},
  doi = {10.1109/CEC.2010.5586191},
  journal = {Evolutionary Computation (CEC), 2010 IEEE Congress on},
  owner = {luigi},
  timestamp = {2010.10.06}

}

@INPROCEEDINGS{onieva10overtaking,

  author = {Onieva, Enrique and Cardamone, Luigi and Loiacono, Daniele and Lanzi,
	Pier Luca},
  title = {Overtaking opponents with blocking strategies using fuzzy logic},
  year = {2010},
  pages = {123 -130},
  month = {aug.},
  doi = {10.1109/ITW.2010.5593364},
  journal = {Computational Intelligence and Games (CIG), 2010 IEEE Symposium on},
  owner = {luigi},
  timestamp = {2010.10.27}

}