BibSLEIGH — Pier_Luca

Travelled to:

1 × France
2 × USA

Collaborated with:

Daniele Loiacono Luigi Cardamone Luca Galli G.Psaila M.Richeldi ∅ Julian Togelius L.Baresi M.Miraz Riccardo Stucchi Edoardo Giacomello Alessandro Pietro Bardelli Enrique Onieva Antonio Caiazzo Matteo Botta Vincenzo Gautieri D.Braga A.Campi S.Ceri M.Klemettinen Michele Pirovano Renato Mainetti Gabriel Baud-Bovy N. Alberto Borghese Leonard Kinnaird-Heether S.M.Lucas Matt Simmerson Diego Perez Liebana R.G.Reynolds Yago Sáez

Talks about:

race (6) data (4) use (4) tournament (3) unreal (3) learn (3) game (3) strategi (2) approach (2) generat (2)

Person: Pier Luca Lanzi

DBLP: Lanzi:Pier_Luca

Facilitated 1 volumes:

Contributed to:

2010

2003

2000

1996

2008

2009

2010

2011

2012

2014

2019

Wrote 18 papers:

ICST-2010-BaresiLM #approach #java #named: TestFul: An Evolutionary Test Approach for Java (LB, PLL, MM), pp. 185–194.
SAC-2003-BragaCCKL #xml: Discovering Interesting Information in XML Data with Association Rules (DB, AC, SC, MK, PLL), pp. 450–454.
SAC-2000-PsailaL #mining: Hierarchy-based Mining of Association Rules in Data Warehouses (GP, PLL), pp. 307–312.
KDD-1996-RicheldiL #effectiveness #feature model: Performing Effective Feature Selection by Investigating the Deep Structure of the Data (MR, PLL), pp. 379–383.
CIG-2008-LoiaconoTLKLSPRS #contest: The WCCI 2008 simulated car racing competition (DL, JT, PLL, LKH, SML, MS, DPL, RGR, YS), pp. 119–126.
CIG-2009-CardamoneLL #learning #using: Learning drivers for TORCS through imitation using supervised methods (LC, DL, PLL), pp. 148–155.
CIG-2009-GalliLL #learning #policy: Learning a context-aware weapon selection policy for Unreal Tournament III (LG, DL, PLL), pp. 310–316.
CIG-2009-LoiaconoTL: Simulated car racing (DL, JT, PLL).
CIG-2010-CardamoneLLB #algorithm #search-based #using: Searching for the optimal racing line using genetic algorithms (LC, DL, PLL, APB), pp. 388–394.
CIG-2010-OnievaCLL #fuzzy #logic #using: Overtaking opponents with blocking strategies using fuzzy logic (EO, LC, DL, PLL), pp. 123–130.
CIG-2011-CardamoneCLL #behaviour #game studies: Transfer of driving behaviors across different racing games (LC, AC, DL, PLL), pp. 227–234.
CIG-2011-GalliLCL #approach #detection #framework #machine learning: A cheating detection framework for Unreal Tournament III: A machine learning approach (LG, DL, LC, PLL), pp. 266–272.
CIG-2012-BottaGLL #evolution #game studies: Evolving the optimal racing line in a high-end racing game (MB, VG, DL, PLL), pp. 108–115.
CIG-2012-PirovanoMBLB #adaptation #game studies #self: Self-adaptive games for rehabilitation at home (MP, RM, GBB, PLL, NAB), pp. 179–186.
CIG-2014-GalliLL #data mining #design pattern #mining: Applying data mining to extract design patterns from Unreal Tournament levels (LG, PLL, DL), pp. 1–8.
CIG-2014-LanziLS #evolution: Evolving maps for match balancing in first person shooters (PLL, DL, RS), pp. 1–8.
CoG-2019-GiacomelloLL #generative #network: Searching the Latent Space of a Generative Adversarial Network to Generate DOOM Levels (EG, PLL, DL), pp. 1–8.
CoG-2019-Lanzi #complexity #using: Evaluating the Complexity of Players' Strategies using MCTS Iterations (PLL), pp. 1–8.