BibSLEIGH — Simon_M

Travelled to:

1 × Canada
1 × Germany
1 × India
1 × Korea
1 × USA
2 × Spain
2 × United Kingdom

Collaborated with:

∅ Diego Perez Liebana Raluca D. Gaina Spyridon Samothrakis Julian Togelius A.C.Downton Thomas Philip Runarsson Diego Pérez-Liébana Samuel A. Roberts David Robles Atif M. Alhejali Philipp Rohlfshagen Ivan Bravi L.Du K.T.Cho T.Huang G.Patoulas K.Sarampalis Peter Burrow Aisha A. Abdullahi Jialin Liu 0001 E.Ishidera Renzo De Nardi Wichit Sombat Piers R. Williams Cristina Guerrero-Romero A.C.Tams G.W.Beccaloni M.J.Scoble G.S.Robinson Alexander Dockhorn Vanessa Volz B.Al-Badr Luis Peña S.Ossowski José María Peña Sánchez M.Fasli Rokas Volkovas Michael Fairbank John R. Woodward S.J.Cho S.Ryu Alexandros Agapitos J.Schmidhuber Andreas Konstantinidis 0002 Daniel Ashlock Wendy Ashlock Colin Lee M.J.Nelson Paolo Burelli K.Karpouzis Peter I. Cowling T.Schaul Matthew Stephenson J.Renz A.Panaretos L.Sosa A.Tang S.Wong R.Young Olve Drageset Ercüment Ilhan Martin Balla G.J.Wells A.C.Holmes Daniele Loiacono P.L.Lanzi Leonard Kinnaird-Heether Matt Simmerson R.G.Reynolds Yago Sáez Chris Bamford Sanaz Mostaghim R.Kruse

Talks about:

game (19) learn (16) play (11) general (9) pac (9) man (9) evolut (8) evalu (8) versus (7) tempor (7)

Person: Simon M. Lucas

DBLP: Lucas:Simon_M=

Facilitated 1 volumes:

Contributed to:

2005

2004

2003

2002

2001

2000

1999

1997

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Wrote 61 papers:

ICDAR-2005-Lucas #contest: Text Locating Competition Results (SML), pp. 80–85.
ICDAR-2005-LucasC #grid #performance: Fast Convolutional OCR with the Scanning N-Tuple Grid (SML, KTC), pp. 799–805.
ICPR-v3-2004-LucasH #recognition #sequence: Sequence Recognition with Scanning N-Tuple Ensembles (SML, TKH), pp. 410–413.
ICDAR-2003-DowntonLPBSR: Computerising Natural History Card Archives (ACD, SML, GP, GWB, MJS, GSR), pp. 354–358.
ICDAR-2003-LucasPD #image #performance #recognition #word: Fast Lexicon-Based Word Recognition in Noisy Index Card Images (SML, GP, ACD), pp. 462–466.
ICDAR-2003-LucasPSTWY #contest #robust: ICDAR 2003 Robust Reading Competitions (SML, AP, LS, AT, SW, RY), pp. 682–687.
ICPR-v3-2002-IshideraLD #generative #image #recognition #word: Likelihood Word Image Generation Model for Word Recognition (EI, SML, ACD), pp. 172–175.
ICPR-v3-2002-Lucas #deployment #evaluation: Web-Based Evaluation and Deployment of Pattern Recognizers (SML), pp. 419–422.
ICDAR-2001-DowntonTWHLBSR #architecture #design #legacy: Constructing Web-Based Legacy Index Card Archives — Architectural Design Issues and Initial Data Acquisition (ACD, ACT, GJW, ACH, SML, GWB, MJS, GSR), pp. 854–858.
ICDAR-2001-LucasTCDR #recognition #robust #word: Robust Word Recognition for Museum Archive Card Indexing (SML, ACT, SJC, ACD, SR), pp. 144–148.
ICPR-v2-2000-LucasS #algorithm #automation #evaluation #internet: Automatic Evaluation of Algorithms over the Internet (SML, KS), pp. 2471–2474.
ICPR-v4-2000-Lucas #graph #performance #taxonomy: Efficient Best-First Dictionary Search Given Graph-Based Input (SML), pp. 4434–4437.
ICDAR-1999-DowntonLD #evaluation #lazy evaluation #recognition: Lazy Evaluation for Best-First Contextual Handwriting Recognition (ACD, SML, LD), pp. 589–592.
ICDAR-1997-DuDLA #documentation #evaluation #lazy evaluation #recognition #semantics #using: Generalized Contextual Recognition of Hand-Printed Documents Using Semantic Trees with Lazy Evaluation (LD, ACD, SML, BAB), pp. 238–242.
CIG-2005-Lucas #evolution #game studies #network: Evolving a Neural Network Location Evaluator to Play Ms. Pac-Man (SML).
CIG-2005-TogeliusL #composition #game studies #symmetry: Forcing Neurocontrollers to Exploit Sensory Symmetry Through Hard-wired Modularity in the Game of Cellz (JT, SML).
CIG-2006-LucasR #co-evolution #difference #evaluation #learning: Temporal Difference Learning Versus Co-Evolution for Acquiring Othello Position Evaluation (SML, TPR), pp. 52–59.
CIG-2007-LucasT #difference #evolution #learning: Point-to-Point Car Racing: an Initial Study of Evolution Versus Temporal Difference Learning (SML, JT), pp. 260–267.
CIG-2007-TogeliusNL #automation #game studies #personalisation #towards: Towards automatic personalised content creation for racing games (JT, RDN, SML), pp. 252–259.
CIG-2008-AgapitosTLSK #evolution #generative #multi: Generating diverse opponents with multiobjective evolution (AA, JT, SML, JS, AK0), pp. 135–142.
CIG-2008-LoiaconoTLKLSPRS #contest: The WCCI 2008 simulated car racing competition (DL, JT, PLL, LKH, SML, MS, DPL, RGR, YS), pp. 119–126.
CIG-2008-Lucas #difference #evolution #learning: Investigating learning rates for evolution and temporal difference learning (SML), pp. 1–7.
CIG-2009-BurrowL #difference #evolution #game studies #learning: Evolution versus Temporal Difference Learning for learning to play Ms. Pac-Man (PB, SML), pp. 53–60.
CIG-2009-Lucas: Screen-capture Ms Pac-Man (SML).
CIG-2009-Lucas09a #contest: Ms Pac-Man versus ghost-team competition (SML).
CIG-2009-Lucas09b #difference #learning: Temporal difference learning with interpolated table value functions (SML), pp. 32–37.
CIG-2009-RoblesL #game studies: A simple tree search method for playing Ms. Pac-Man (DR, SML), pp. 249–255.
CIG-2010-Lucas #evolution #learning #problem: Estimating learning rates in evolution and TDL: Results on a simple grid-world problem (SML), pp. 372–379.
CIG-2010-SamothrakisRL: A UCT agent for Tron: Initial investigations (SS, DR, SML), pp. 365–371.
CIG-2011-AbdullahiL #difference #learning: Temporal difference learning with interpolated n-tuples: Initial results from a simulated car racing environment (AAA, SML), pp. 321–328.
CIG-2011-AlhejaliL #programming #search-based #using: Using a training camp with Genetic Programming to evolve Ms Pac-Man agents (AMA, SML), pp. 118–125.
CIG-2011-RoblesRL #game studies #learning #monte carlo: Learning non-random moves for playing Othello: Improving Monte Carlo Tree Search (DR, PR, SML), pp. 305–312.
CIG-2012-AshlockASLL #co-evolution #contest: From competition to cooperation: Co-evolution in a rewards continuum (DA, WA, SS, SML, CL), pp. 33–40.
CIG-2012-NelsonBKLC: Tutorials (MJN, PB, KK, SML, PIC).
CIG-2012-PenaOPL #evolution #game studies #learning: Learning and evolving combat game controllers (LP, SO, JMPS, SML), pp. 195–202.
CIG-2012-PerezRL #monte carlo: Monte Carlo Tree Search: Long-term versus short-term planning (DPL, PR, SML), pp. 219–226.
CIG-2012-RobertsL #behaviour #design #evolution: Evolving spaceship designs for optimal control and the emergence of interesting behaviour (SAR, SML), pp. 342–349.
CIG-2012-RunarssonL #difference #game studies #learning: Imitating play from game trajectories: Temporal difference learning versus preference learning (TPR, SML), pp. 79–82.
CIG-2012-SombatRL: Evaluating the enjoyability of the ghosts in Ms Pac-Man (WS, PR, SML), pp. 379–387.
CIG-2013-AlhejaliL #heuristic #monte carlo #programming #search-based #using: Using genetic programming to evolve heuristics for a Monte Carlo Tree Search Ms Pac-Man agent (AMA, SML), pp. 1–8.
CIG-2013-PerezSL #learning #monte carlo #multi #online: Online and offline learning in multi-objective Monte Carlo Tree Search (DPL, SS, SML), pp. 1–8.
CIG-2013-RobertsL #game studies #problem: Measuring interestingness of continuous game problems (SAR, SML), pp. 1–8.
CIG-2014-PerezSL #game studies #knowledge-based #performance #video: Knowledge-based fast evolutionary MCTS for general video game playing (DPL, SS, SML), pp. 1–8.
CIG-2014-SamothrakisRPL #game studies: Rolling horizon methods for games with continuous states and actions (SS, SAR, DPL, SML), pp. 1–8.
CIG-2015-RunarssonL #approximate #evaluation #game studies #on the #using: On imitating Connect-4 game trajectories using an approximate n-tuple evaluation function (TPR, SML), pp. 208–213.
CIG-2015-SamothrakisLLF #game studies #video: Neuroevolution for General Video Game Playing (SS, DPL, SML, MF), pp. 200–207.
CIG-2016-LiebanaSTSL #game studies #robust #video: Analyzing the robustness of general video game playing agents (DPL, SS, JT, TS, SML), pp. 1–8.
CIG-2016-WilliamsLL #contest: Ms. Pac-Man Versus Ghost Team CIG 2016 competition (PRW, DPL, SML), pp. 1–8.
CIG-2017-GainaLL #evolution #game studies #video: Rolling horizon evolution enhancements in general video game playing (RDG, SML, DPL), pp. 88–95.
CIG-2017-LiebanaSGRL #game studies #physics #video: Introducing real world physics and macro-actions to general video game ai (DPL, MS, RDG, JR, SML), pp. 248–255.
AIIDE-2018-GainaLP #algorithm #named #visualisation: VERTIGØ: Visualisation of Rolling Horizon Evolutionary Algorithms in GVGAI (RDG, SML, DPL), pp. 265–267.
CIG-2018-BraviLL0 #analysis #game studies #video: Shallow Decision-Making Analysis in General Video Game Playing (IB, DPL, SML, JL0), pp. 1–8.
CIG-2018-GainaLP #experience #predict: General Win Prediction from Agent Experience (RDG, SML, DPL), pp. 1–8.
CIG-2018-Guerrero-Romero #algorithm #design #game studies #testing #using: Using a Team of General AI Algorithms to Assist Game Design and Testing (CGR, SML, DPL), pp. 1–8.
CIG-2018-Lucas #game studies #performance #research: Game AI Research with Fast Planet Wars Variants (SML), pp. 1–4.
AIIDE-2019-LiebanaGDIBL #analysis #statistics: Analysis of Statistical Forward Planning Methods in Pommerman (DPL, RDG, OD, EI, MB, SML), pp. 66–72.
CoG-2019-BraviLL0 #game studies #named #optimisation #statistics: Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor (IB, DPL, SML, JL0), pp. 1–8.
CoG-2019-DockhornLVBGL #game studies #learning #modelling: Learning Local Forward Models on Unforgiving Games (AD, SML, VV, IB, RDG, DPL), pp. 1–4.
CoG-2019-GainaLP: Project Thyia: A Forever Gameplayer (RDG, SML, DPL), pp. 1–8.
CoG-2019-LucasDVBGBPMK #approach #game studies #learning: A Local Approach to Forward Model Learning: Results on the Game of Life Game (SML, AD, VV, CB, RDG, IB, DPL, SM, RK), pp. 1–8.
CoG-2019-VolkovasFWL #2d #game studies #named #prototype: Mek: Mechanics Prototyping Tool for 2D Tile-Based Turn-Based Deterministic Games (RV, MF, JRW, SML), pp. 1–8.