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School of Electronic Engineering and Computer Science

Dr Diego Perez-Liebana

Diego

Senior Lecturer

Email: diego.perez@qmul.ac.uk
Room Number: Peter Landin, CS 301
Twitter: @diego_pliebana
Office Hours: Tuesday 09:00-11:00

Profile

Born in Madrid (Spain) in 1983 and living in London (United Kingdom). I am a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London (UK). I hold a Ph.D in Computer Science from the University of Essex (2015) and a Master degree in Computer Science from University Carlos III (Madrid, Spain; 2007).

My research is centred in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation. I am especially interested on the application of Statsitical Forward Planning methods (such as Monte Carlo Tree Search and Rolling Horizon Evolutionary Algorithms) to modern games, and also on General Video Game Playing, which involves the creation of content and agents that play any real-time game that is given to it. I am author of more than 90 papers in the field of Game AI, published in the main conferences of the field of Computational Intelligence in Games and Evolutionary Computation, and I was once general chair of IEEE CoG 2020. I have publications in highly respected journals such as IEEE TCIAIG (the top journal on the Game AI field) and IEEE TEC (which counts with one of highest impact factors in Computer Science). I have also organised international competitions for the Game AI research community, such as the Physical Travelling Salesman Competition, and the General Video Game AI Competition, held in IEEE (WCCI, CIG) and ACM (GECCO) International Conferences.

I also experience in the videogames industry as a game programmer (Revistronic; Madrid, Spain), with titles published for both PC and consoles. I worked as a software engineer (Game Brains; Dublin, Ireland), where I was in charge of developing AI tools that can be applied to the latest industry videogames. As a lecturer I teach modules related to game development and the application of Artificial Intelligence to Games.

Teaching

Advanced Game Development (Postgraduate)

This module covers games programming in C++, assuming the student has experience with object-oriented programming. The module introduces the C++ language and uses it to explores a range of topics in games programming, including 2D and 3D graphics, OpenGL, physics, input systems, and the use of C++ in modern game engines. It emphasises a practical approach to programming, with the students developing playable games for the final assessment.

Artificial Intelligence in Games (Postgraduate)

This module covers a range of Artificial Intelligence techniques employed in games, and teaches how games are and can be used for research in Artificial Intelligence. This module has a strong programming component. The module explores algorithms for creating agents that play classical board games (such as chess or checkers) and real-time games (Mario or PacMan), including single agents able to play multiple games. The module gives an overview of multiple techniques, such as Monte Carlo Tree Search, Evolutionary Computation, Deep and Machine Learning applied to games.

Game Development (Postgraduate)

This module provides a practical foundation in the development of video games, covering modern technical approaches and development practices. It is delivered in two intensive blocks. Part 1 introduces programming games within an industry standard game engine, focusing on core topics such as game logic, player interaction, NPC behaviour, and the use of prototyping and playtesting during development. Part 2 explores a range of advanced topics, such as applications of machine learning and AI in game development, procedural content generation, and interaction technologies. Each part is assessed separately, with students working in groups to develop playable digital prototypes.

Multi-platform Game Development (Undergraduate)

This module covers the fundamentals of game development in a multi-platform (consoles, PC, Web and mobile devices) environment. The course focuses on development of 3D games, covering all aspects of game development: the game loop, math, physics, audio, graphics, input, animations, particle systems and artificial intelligence. This module has a strong programming content, required for laboratories and assignments. The practical aspects will be taught using a popular game development platform. The main assignment of this module consists of the development of a full 3D game at the student's choice.

Multi-platform Game Development (Postgraduate)

This module covers the fundamentals of game development in a multi-platform (consoles, PC, Web and mobile devices) environment). The course focuses on development of 3D games, covering all aspects of game development: the game loop, math, physics, audio, graphics, input, animations, particle systems and artificial intelligence. This module has a strong programming content, required for laboratories and assignments. The practical aspects will be taught using a popular game development platform. The main assignment of this module consists of the development of a full 3D game at the student's choice.

Research

Research Interests:

My research is centred in the application of Artificial Intelligence to games, Reinforcement Learning and Evolutionary Computation. At the moment, I am especially interested on General Video Game Playing, which involves the creation of content and agents that play any real-time game that is given to it. He has published more than 60 papers in leading conferences and journals with 2 best paper awards, a BCS Intelligence Prize, and 1,900+ citations. Applying search algorithms, evolutionary computation and reinforcement learning to games, he is the main organizer of popular game AI competitions (GVGAI, MARLO) - securing substantial industry funding by MSR and Google Deepmind, general chair of the 2019 IEEE Conference on Games, track chair of academic (IEEE-CEEC, IEEE-CIG, ACM-FDG) and industry (nucl.ai) game conferences, organiser of game AI workshops and meetups, and frequently invited speaker at industry events like the London Games Festival. He is currently co-supervising 5 PhD students. As QMUL?s IGGI industry liaison, he is drawing on his extensive games industry experience, with several published PC and console titles and developed game AI tools under his belt.

Publications

    • Goodman J, Perez D, Lucas SM (2022), Visualising Multiplayer Game Spaces $nameOfConference


    • Goodman J, Perez-Liebana D, Lucas S (2022), MultiTree MCTS in Tabletop Games 2022 IEEE Conference on Games (CoG)


    • Balla M, Perez-Liebana D (2022), Task Relabelling for Multi-task Transfer using Successor Features 2022 IEEE Conference on Games (CoG)


    • Balla M, Perez-Liebana D (2022), Task Relabelling for Multi-task Transfer using Successor Features $nameOfConference


    • Goodman J, Perez-Liebana D, Lucas S (2022), Visualising Multiplayer Game Spaces $nameOfConference


    • Ilhan E, Gow J, Perez D (2021), Student-Initiated Action Advising via Advice Novelty $nameOfConference


    • Guerrero Romero C, Perez-Liebana D (2021), MAP-Elites to Generate a Team of Agents that Elicits Diverse Automated Gameplay 2021 IEEE Conference on Games (CoG)


    • Dockhorn A, Hurtado-Grueso J, Jeurissen D et al. (2021), Portfolio Search and Optimization for General Strategy Game-Playing $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2021), Action Advising with Advice Imitation in Deep Reinforcement Learning $nameOfConference


    • Perez-Liebana D, Guerrero-Romero C, Dockhorn A et al. (2021), Generating Diverse and Competitive Play-Styles for Strategy Games $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2021), Learning on a Budget via Teacher Imitation $nameOfConference


    • Gaina RD, Devlin S, Lucas SM et al. (2021), Rolling Horizon Evolutionary Algorithms for General Video Game Playing $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2021), Action advising with advice imitation in deep reinforcement learning Autonomous Agents and Multiagent Systems

    • Jeurissen D, Winands MHM, Sironi CF et al. (2021), Automatic Goal Discovery in Subgoal Monte Carlo Tree Search $nameOfConference


    • Pacheco C, Melhart D, Liapis A et al. (2021), Discrete versus Ordinal Time-Continuous Believability Assessment $nameOfConference


    • Goodman J, Perez-Liebana D, Lucas S (2021), Fingerprinting Tabletop Games $nameOfConference


    • Dockhorn A, Hurtado-Grueso J, Jeurissen D et al. (2021), Game State and Action Abstracting Monte Carlo Tree Search for General Strategy Game-Playing $nameOfConference


    • Perez-Liebana D, Guerrero-Romero C, Dockhorn A et al. (2021), Generating Diverse and Competitive Play-Styles for Strategy Games $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2021), Learning on a Budget via Teacher Imitation $nameOfConference


    • Dockhorn A, Hurtado-Grueso J, Jeurissen D et al. (2021), Portfolio Search and Optimization for General Strategy Game-Playing $nameOfConference


    • Ringer C, Dobre GC, Pacheco C et al. (2021), Rolling horizon co-evolution in two-player general video game playing $nameOfConference

    • Gaina RD, Goodman J, Perez-Liebana D (2021), TAG: Terraforming Mars $nameOfConference

    • Pacheco C, Melhart D, Liapis A et al. (2021), Trace It Like You Believe It: Time-Continuous Believability Prediction $nameOfConference


    • Tot M, Conserva M, Chitayat AP et al. (2021), What Are You Looking At? Team Fight Prediction Through Player Camera $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2020), Student-Initiated Action Advising via Advice Novelty $nameOfConference


    • Guerrero Romero C, Kumari S, Perez-Liebana D et al. (2020), Studying General Agents in Video Games from the Perspective of Player Experience AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

    • Gaina RD, Balla M, Dockhorn A et al. (2020), Design and Implementation of TAG: A Tabletop Games Framework $nameOfConference


    • Estaben A, Díaz C, Montoliu R et al. (2020), TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI $nameOfConference


    • Perez-Liebana D, Dockhorn A, Grueso JH et al. (2020), The Design Of "Stratega": A General Strategy Games Framework $nameOfConference


    • Perez-Liebana D, Dockhorn A, Jeurissen D et al. (2020), Stratega - A General Strategy Games Framework AIIDE-20 Workshop on Artificial Intelligence for Strategy Games (2020)

    • Balla M, Lucas SM, Perez-Liebana D (2020), Evaluating Generalisation in General Video Game Playing $nameOfConference


    • Perez-Liebana D, Alam MS, Gaina RD (2020), Rolling Horizon NEAT for General Video Game Playing $nameOfConference


    • Gaina RD, Perez-Liebana D, Lucas SM et al. (2020), Self-Adaptive Rolling Horizon Evolutionary Algorithms for General Video Game Playing $nameOfConference


    • Balla M, Lucas SM, Perez-Liebana D (2020), Evaluating Generalisation in General Video Game Playing $nameOfConference


    • Perez-Liebana D, Alam MS, Gaina RD (2020), Rolling Horizon NEAT for General Video Game Playing $nameOfConference


    • Houghton B, Milani S, Topin N et al. (2020), Guaranteeing Reproducibility in Deep Learning Competitions $nameOfConference


    • Montoliu R, Gaina RD, Pérez-Liebana D et al. (2020), Efficient Heuristic Policy Optimisation for a Challenging Strategic Card Game International Conference on the Applications of Evolutionary Computation


    • Gaina RD, Devlin S, Lucas SM et al. (2020), Rolling Horizon Evolutionary Algorithms for General Video Game Playing $nameOfConference


    • Hsu YJ, Perez-Liebana D (2020), MCTS pruning in turn-based strategy games $nameOfConference

    • Gaina RD, Balla M, Dockhorn A et al. (2020), TAG: A tabletop games framework $nameOfConference

    • Perez-Liebana D, Hsu YJ, Emmanouilidis S et al. (2020), Tribes: A new turn-based strategy game for AI research $nameOfConference

    • Liu J, Perez-Liebana D, Cazenave T et al. (2019), Guest editorial special issue on game competition frameworks for research and education $nameOfConference


    • Dockhorn A, Lucas SM, Volz V et al. (2019), Learning Local Forward Models on Unforgiving Games $nameOfConference


    • Lucas S, Dockhorn A, Volz V et al. (2019), A Local Approach to Forward Model Learning: Results on the Game of Life Game IEEE Conference on Games (COG)


    • Dockhorn A, Lucas S, Volz V et al. (2019), Learning Local Forward Models on Unforgiving Games IEEE Conference on Games (COG)


    • Drageset O, GAINA RALUCA, Perez-Liebana D et al. (2019), Optimising Level Generators for General Video Game AI IEEE Conference on Games (COG)


    • GAINA RALUCA, Lucas S, Perez-Liebana D (2019), Project Thyia: A Forever Gameplayer IEEE Conference on Games (COG)


    • Anderson D, Rodgers P, Levine J et al. (2019), Ensemble decision systems for general video game playing 2019 IEEE Conference on Games (CoG)


    • Neufeld X, Mostaghim S, Perez-Liebana D (2019), Evolving game state evaluation functions for a hybrid planning approach $nameOfConference


    • Bravi I, Perez-Liebana D, Lucas SM et al. (2019), Rinascimento: Optimising statistical forward planning agents for playing splendor $nameOfConference


    • Ilhan E, Gow J, Perez-Liebana D (2019), Teaching on a budget in multi-agent deep reinforcement learning $nameOfConference


    • Khalifa A, Green MC, Perez-Liebana D et al. (2019), General Video Game Rule Generation $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D (2019), Project Thyia: A Forever Gameplayer $nameOfConference


    • Anderson D, Guerrero-Romero C, Perez-Liebana D et al. (2019), Ensemble Decision Systems for General Video Game Playing $nameOfConference


    • İlhan E, Gow J, Perez-Liebana D (2019), Teaching on a Budget in Multi-Agent Deep Reinforcement Learning $nameOfConference


    • Bravi I, Lucas S, Perez-Liebana D et al. (2019), Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor $nameOfConference


    • Lucas SM, Dockhorn A, Volz V et al. (2019), A Local Approach to Forward Model Learning: Results on the Game of Life Game $nameOfConference


    • Perez D, Liu J, Abdel Samea Khalifa A et al. (2019), General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms $nameOfConference


    • Lucas S, Liu J, Bravi I et al. (2019), Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best Game Simulations Workshop (AAAI)

    • Perez-Liebana D, Hofmann K, Mohanty SP et al. (2019), The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition $nameOfConference


    • Lucas SM, Liu J, Bravi I et al. (2019), Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best $nameOfConference


    • Perez-Liebana D, Gaina RD, Drageset O et al. (2019), Analysis of statistical forward planning methods in pommerman $nameOfConference

    • Gaina RD, Lucas SM, Pérez-Liébana D (2019), Tackling sparse rewards in real-time games with statistical forward planning methods $nameOfConference


    • Torrado RR, Bontrager P, Togelius J et al. (2018), Deep Reinforcement Learning for General Video Game AI $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D (2018), General Win Prediction from Agent Experience $nameOfConference


    • Bravi I, Perez-Liebana D, Lucas SM et al. (2018), Shallow Decision-Making Analysis in General Video Game Playing $nameOfConference


    • Ashlock D, Kim EY, Perez-Lebana D (2018), Toward General Mathematical Game Playing Agents $nameOfConference


    • Lucas SM, Liu J, Perez-Liebana D (2018), The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation $nameOfConference


    • Rohlfshagen P, Liu J, Perez-Liebana D et al. (2018), Pac-Man conquers academia: Two decades of research using a classic arcade game $nameOfConference


    • Guerrero-Romero C, LUCAS S, PEREZ-LIEBANA D (2018), Using a Team of General AI Algorithms to Assist Game Design and Testing 2018 IEEE Conference on Computational Intelligence and Games (CIG)


    • Pacheco C, Tokarchuk L, Pérez-Liébana D (2018), Studying believability assessment in racing games $nameOfConference


    • Torrado RR, Bontrager P, Togelius J et al. (2018), Deep Reinforcement Learning for General Video Game AI $nameOfConference


    • Bravi I, Liu J, Perez-Liebana D et al. (2018), Shallow decision-making analysis in General Video Game Playing $nameOfConference


    • Perez-Liebana D, Liu J, Khalifa A et al. (2018), General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms $nameOfConference


    • Lucas SM, Liu J, Perez-Liebana D (2018), The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation $nameOfConference


    • Lucas SM, Liu J, Perez-Liebana D (2018), Efficient noisy optimisation with the multi-sample and sliding window compact genetic algorithms $nameOfConference


    • Tornado RR, Bontrager P, Togelius J et al. (2018), Deep Reinforcement Learning for General Video Game AI $nameOfConference

    • Perez-Liebana D, Nicolau M (2018), Evolving behaviour tree structures using grammatical evolution $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D et al. (2018), General Win Prediction from Agent Experience $nameOfConference

    • Kunanusont K, Lucas SM, Pérez-Lébana D (2018), Modeling player experience with the n-tuple bandit evolutionary algorithm $nameOfConference

    • Sironi CF, Liu J, Perez-Liebana D et al. (2018), Self-adaptive MCTS for General Video Game Playing $nameOfConference


    • Guerrero-Romero C, Lucas SM, Perez-Liebana D et al. (2018), Using a Team of General AI Algorithms to Assist Game Design and Testing $nameOfConference

    • Gaina RD, Lucas SM, Pérez-Liébana D (2018), Vertigø: Visualisation of rolling horizon evolutionary algorithms in GVGAI $nameOfConference

    • Volkovas R, Fairbank M, Perez-Liebana D (2017), Diversity maintenance using a population of repelling random-mutation hill climbers $nameOfConference


    • Neufeld X, Mostaghim S, Perez-Liebana D (2017), HTN fighter: Planning in a highly-dynamic game $nameOfConference


    • Gonzalez-Castro JM, Perez-Liebana D (2017), Opponent models comparison for 2 players in GVGAI competitions $nameOfConference


    • Gaina RD, Couetoux A, Soemers D et al. (2017), The 2016 Two-Player GVGAI Competition $nameOfConference


    • Horsley L, Perez-Liebana D (2017), Building an automatic sprite generator with deep convolutional generative adversarial networks $nameOfConference


    • Ashlock D, Perez-Liebana D, Saunders A (2017), General video game playing escapes the no free lunch theorem $nameOfConference


    • Khalifa A, Green MC, Perez-Liebana D et al. (2017), General video game rule generation $nameOfConference


    • Perez-Liebana D, Stephenson M, Gaina RD et al. (2017), Introducing real world physics and macro-actions to general video game ai $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D (2017), Rolling horizon evolution enhancements in general video game playing $nameOfConference


    • Guerrero-Romero C, Louis A, Perez-Liebana D (2017), Beyond Playing to Win: Diversifying Heuristics for GVGAI IEEE Conference on Computational Intelligence and Games (CIG)


    • Lucas SM, Liu J, Pérez-Liébana D (2017), Efficient Noisy Optimisation with the Sliding Window Compact Genetic Algorithm $nameOfConference


    • Liu J, Perez-Liebana D, Lucas SM (2017), Bandit-based Random Mutation Hill-Climbing $nameOfConference


    • Walton-Rivers J, Williams PR, Bartle R et al. (2017), Evaluating and modelling Hanabi-playing agents $nameOfConference


    • Liu J, Togelius J, Perez-Liebana D et al. (2017), Evolving Game Skill-Depth using General Video Game AI agents $nameOfConference


    • Kunanusont K, Lucas SM, Perez-Liebana D (2017), General Video Game AI: Learning from screen capture $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D (2017), Population seeding techniques for Rolling Horizon Evolution in General Video Game Playing $nameOfConference


    • Kunanusont K, Gaina RD, Liu J et al. (2017), The N-Tuple bandit evolutionary algorithm for automatic game improvement $nameOfConference


    • Lucas SM, Liu J, Pérez-Liébana D (2017), Evaluating Noisy Optimisation Algorithms: First Hitting Time is Problematic $nameOfConference


    • Gaina RD, Liu J, Lucas SM et al. (2017), Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing $nameOfConference


    • Walton-Rivers J, Williams PR, Bartle R et al. (2017), Evaluating and Modelling Hanabi-Playing Agents $nameOfConference


    • Kunanusont K, Lucas SM, Perez-Liebana D (2017), General Video Game AI: Learning from Screen Capture $nameOfConference


    • Gaina RD, Lucas SM, Perez-Liebana D (2017), Population Seeding Techniques for Rolling Horizon Evolution in General Video Game Playing $nameOfConference


    • Liu J, Togelius J, Perez-Liebana D et al. (2017), Evolving Game Skill-Depth using General Video Game AI Agents $nameOfConference


    • Kunanusont K, Gaina RD, Liu J et al. (2017), The N-Tuple Bandit Evolutionary Algorithm for Automatic Game Improvement $nameOfConference


    • Gaina RD, Pérez-Liébana D, Lucas SM (2017), General video game for 2 players: Framework and competition $nameOfConference


    • Liu J, Pérez-Liébana D, Lucas SM (2017), Rolling horizon coevolutionary planning for two-player video games $nameOfConference


    • Gaina RD, Liu J, Lucas SM et al. (2017), Analysis of vanilla rolling Horizon evolution parameters in general video game playing $nameOfConference


    • Samothrakis S, Fasli M, Perez D et al. (2016), Default policies for global optimisation of noisy functions with severe noise $nameOfConference


    • Perez-Liebana D, Mostaghim S, Lucas SM (2016), Multi-objective tree search approaches for general video game playing $nameOfConference


    • Williams PR, Perez-Liebana D, Lucas SM (2016), Ms. Pac-Man Versus Ghost Team CIG 2016 Competition $nameOfConference


    • Perez-Liebana D, Samothrakis S, Togelius J et al. (2016), The 2014 General Video Game Playing Competition $nameOfConference


    • Liu J, Fairbank M, Pérez-Liébana D et al. (2016), Optimal resampling for the noisy OneMax problem $nameOfConference


    • Khalifa A, Perez-Liebana D, Lucas SM et al. (2016), General video game level generation $nameOfConference


    • Liu J, Pérez-Liébana D, Lucas SM (2016), Rolling Horizon Coevolutionary Planning for Two-Player Video Games $nameOfConference


    • Perez-Liebana D, Samothrakis S, Togelius J et al. (2016), Analyzing the robustness of general video game playing agents $nameOfConference


    • Horn H, Volz V, Perez-Liebana D et al. (2016), MCTS/EA hybrid GVGAI players and game difficulty estimation $nameOfConference


    • Williams PR, Perez-Liebana D, Lucas SM (2016), Ms. Pac-Man Versus Ghost Team CIG 2016 competition $nameOfConference


    • Liu J, Peŕez-Liebana D, Lucas SM (2016), Bandit-Based Random Mutation Hill-Climbing $nameOfConference


    • Nicolau M, Perez-Liebana D, Oneill M et al. (2016), Evolutionary Behavior Tree Approaches for Navigating Platform Games $nameOfConference


    • Samothrakis S, Perez D, Lucas SM et al. (2016), Predicting Dominance Rankings for Score-Based Games $nameOfConference


    • Perez-Liebana D, Samothrakis S, Togelius J et al. (2016), General video game AI: Competition, challenges, and opportunities $nameOfConference


    • Perez D, Mostaghim S, Samothrakis S et al. (2015), Multiobjective Monte Carlo Tree Search for Real-Time Games $nameOfConference


    • Williams PR, Walton-Rivers J, Perez-Liebana D et al. (2015), Monte Carlo Tree Search applied to co-operative problems $nameOfConference


    • Neufeld X, Mostaghim S, Perez-Liebana D (2015), Procedural level generation with answer set programming for general Video Game playing $nameOfConference


    • Samothrakis S, Perez-Liebana D, Lucas SM et al. (2015), Neuroevolution for General Video Game Playing $nameOfConference


    • Perez D, Dieskau J, Hünermund M et al. (2015), Open loop search for general video game playing $nameOfConference


    • Perez D, Samothrakis S, Lucas S (2014), Knowledge-based fast evolutionary MCTS for general video game playing $nameOfConference


    • Samothrakis S, Roberts SA, Perez D et al. (2014), Rolling horizon methods for games with continuous states and actions $nameOfConference


    • Perez D, Togelius J, Samothrakis S et al. (2014), Automated map generation for the physical traveling salesman problem $nameOfConference


    • Perez D, Powley E, Whitehouse D et al. (2014), The 2013 Multi-objective Physical Travelling Salesman Problem Competition $nameOfConference


    • Lucas SM, Samothrakis S, Pérez D (2014), Fast evolutionary adaptation for Monte Carlo Tree Search $nameOfConference


    • Perez D, Powley EJ, Whitehouse D et al. (2014), Solving the physical traveling salesman problem: Tree search and macro actions $nameOfConference


    • Perez D, Samothrakis S, Lucas S (2013), Online and offline learning in multi-objective Monte Carlo Tree Search $nameOfConference


    • Perez D, Samothrakis S, Lucas SM et al. (2013), Rolling horizon evolution versus tree search for navigation in single-player real-time games $nameOfConference


    • Perez D, Rohlfshagen P, Lucas SM (2012), Monte Carlo Tree Search: Long-term versus short-term planning $nameOfConference


    • Perez D, Rohlfshagen P, Lucas SM (2012), The physical travelling salesman problem: WCCI 2012 competition $nameOfConference


    • Lucas SM, Rohlfshagen P, Perez D (2012), Towards more intelligent adaptive video game agents: A computational intelligence perspective $nameOfConference


    • Perez D, Rohlfshagen P, Lucas SM (2012), Monte-Carlo tree search for the physical travelling salesman problem $nameOfConference


    • Browne CB, Powley E, Whitehouse D et al. (2012), A survey of Monte Carlo tree search methods $nameOfConference


    • Perez D, Nicolau M, O'Neill M et al. (2011), Reactiveness and navigation in computer games: Different needs, different approaches $nameOfConference


    • Perez D, Nicolau M, O’Neill M et al. (2011), Evolving behaviour trees for the Mario AI competition using grammatical evolution $nameOfConference


    • Loiacono D, Lanzi PL, Togelius J et al. (2010), The 2009 simulated car racing championship $nameOfConference


    • Perez D, Recio G, Saez Y et al. (2009), Evolving a fuzzy controller for a car racing competition $nameOfConference


    • Perez D, Saez Y, Recio G et al. (2008), Evolving a rule system controller for automatic driving in a car racing competition $nameOfConference


    • Saez Y, Perez D, Sanjuan O et al. (2008), Driving cars by means of genetic algorithms $nameOfConference


    • Loiacono D, Togelius J, Lanzi PL et al. (2008), The WCCI 2008 simulated car racing competition $nameOfConference


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