no code implementations • 23 Apr 2024 • Sam Earle, Filippos Kokkinos, Yuhe Nie, Julian Togelius, Roberta Raileanu
In contrast, text-to-3D methods allow users to specify desired characteristics in natural language, offering a high amount of flexibility and expressivity.
no code implementations • 17 Apr 2024 • Graham Todd, Tim Merino, Sam Earle, Julian Togelius
This is because the four categories ascend in complexity, with the most challenging category often requiring thinking about words in uncommon ways or as parts of larger phrases.
no code implementations • 5 Mar 2024 • Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro, Yi Xia, Pratch Suntichaikul, Ruck Thawonmas, Julian Togelius, Jochen Renz
We thoroughly evaluate the effectiveness of the new metric and the improved classifier.
no code implementations • 4 Mar 2024 • Asad Anjum, Yuting Li, Noelle Law, M Charity, Julian Togelius
This paper studies how large language models (LLMs) can act as effective, high-level creative collaborators and ``muses'' for game design.
no code implementations • 28 Feb 2024 • Roberto Gallotta, Graham Todd, Marvin Zammit, Sam Earle, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis
Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic.
no code implementations • 4 Dec 2023 • Sam Earle, M Charity, Dipika Rajesh, Mayu Wilson, Julian Togelius
We explore the generation of diverse environments using the Amorphous Fortress (AF) simulation framework.
no code implementations • 20 Nov 2023 • Julian Togelius, Ahmed Khalifa, Sam Earle, Michael Cerny Green, Lisa Soros
Evolutionary machine learning (EML) has been applied to games in multiple ways, and for multiple different purposes.
no code implementations • 20 Nov 2023 • Sudipta Banerjee, Anubhav Jain, Zehua Jiang, Nasir Memon, Julian Togelius, Arun Ross
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security.
1 code implementation • 7 Nov 2023 • Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, BingCheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
In this paper, we present the results of the NeurIPS-2022 Neural MMO Challenge, which attracted 500 participants and received over 1, 600 submissions.
no code implementations • 30 Aug 2023 • Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, HanMo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions.
no code implementations • 16 Aug 2023 • Anubhav Jain, Nasir Memon, Julian Togelius
We do so by generating balanced data from an existing imbalanced deep generative model using an evolutionary algorithm and then using this data to train a balanced generative model.
no code implementations • 16 Aug 2023 • M Charity, Yash Bhartia, Daniel Zhang, Ahmed Khalifa, Julian Togelius
This paper introduces a system used to generate game feature suggestions based on a text prompt.
1 code implementation • 8 Aug 2023 • Timothy Merino, Roman Negri, Dipika Rajesh, M Charity, Julian Togelius
The five-dollar model is a lightweight text-to-image generative architecture that generates low dimensional images from an encoded text prompt.
no code implementations • 3 Aug 2023 • Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis, Ahmed Khalifa
We explore AI-powered upscaling as a design assistance tool in the context of creating 2D game levels.
no code implementations • 2 Aug 2023 • Debosmita Bhaumik, Ahmed Khalifa, Julian Togelius
We present Lode Encoder, a gamified mixed-initiative level creation system for the classic platform-puzzle game Lode Runner.
no code implementations • 19 Jul 2023 • Shuo Huang, Chengpeng Hu, Julian Togelius, Jialin Liu
Procedurally generating cities in Minecraft provides players more diverse scenarios and could help understand and improve the design of cities in other digital worlds and the real world.
no code implementations • 22 Jun 2023 • M Charity, Dipika Rajesh, Sam Earle, Julian Togelius
We introduce a system called Amorphous Fortress -- an abstract, yet spatial, open-ended artificial life simulation.
1 code implementation • 1 Jun 2023 • Muhammad U. Nasir, Sam Earle, Christopher Cleghorn, Steven James, Julian Togelius
By merging the code-generating abilities of LLMs with the diversity and robustness of QD solutions, we introduce \texttt{LLMatic}, a Neural Architecture Search (NAS) algorithm.
no code implementations • 29 May 2023 • Matthew Siper, Sam Earle, Zehua Jiang, Ahmed Khalifa, Julian Togelius
The PoD method is very data-efficient in terms of original training examples and well-suited to functional artifacts composed of categorical data, such as game levels and discrete 3D structures.
no code implementations • 20 May 2023 • Muhammad U Nasir, Julian Togelius
Large Language Models (LLMs) have proven to be useful tools in various domains outside of the field of their inception, which was natural language processing.
1 code implementation • 12 May 2023 • Anubhav Jain, Nasir Memon, Julian Togelius
Facial recognition systems have made significant strides thanks to data-heavy deep learning models, but these models rely on large privacy-sensitive datasets.
no code implementations • 12 May 2023 • David Melhart, Julian Togelius, Benedikte Mikkelsen, Christoffer Holmgård, Georgios N. Yannakakis
Video games are one of the richest and most popular forms of human-computer interaction and, hence, their role is critical for our understanding of human behaviour and affect at a large scale.
no code implementations • 31 Mar 2023 • Julian Togelius, Georgios N. Yannakakis
This is not an exhaustive list of strategies, and you may not agree with all of them, but it serves to start a discussion.
1 code implementation • 28 Mar 2023 • Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro, Ruck Thawonmas, Julian Togelius, Jochen Renz
An experiment is conducted to determine the effectiveness of several modified versions of this sample prompt on level stability and similarity by testing them on several characters.
no code implementations • 11 Feb 2023 • Graham Todd, Sam Earle, Muhammad Umair Nasir, Michael Cerny Green, Julian Togelius
Large Language Models (LLMs) are powerful tools, capable of leveraging their training on natural language to write stories, generate code, and answer questions.
no code implementations • 17 Jan 2023 • Sam Earle, Ozlem Yildiz, Julian Togelius, Chinmay Hegde
As a step toward developing such networks, we hand-code and learn models for Breadth-First Search (BFS), i. e. shortest path finding, using the unified architectural framework of Neural Cellular Automata, which are iterative neural networks with equal-size inputs and outputs.
1 code implementation • 5 Dec 2022 • Anubhav Jain, Nasir Memon, Julian Togelius
Face swapping technology used to create "Deepfakes" has advanced significantly over the past few years and now enables us to create realistic facial manipulations.
no code implementations • 11 Oct 2022 • Alberto Alvarez, Jose Font, Julian Togelius
This paper presents Story Designer, a mixed-initiative co-creative narrative structure tool built on top of the Evolutionary Dungeon Designer (EDD) that uses tropes, narrative conventions found across many media types, to design these structures.
no code implementations • 11 Sep 2022 • M Charity, Nasir Memon, Zehua Jiang, Abhi Sen, Julian Togelius
This work expands on previous advancements in genetic fingerprint spoofing via the DeepMasterPrints and introduces Diversity and Novelty MasterPrints.
no code implementations • 11 Sep 2022 • M Charity, Julian Togelius
The Keke AI Competition introduces an artificial agent competition for the game Baba is You - a Sokoban-like puzzle game where players can create rules that influence the mechanics of the game.
no code implementations • 9 Aug 2022 • M Charity, Julian Togelius
This paper describes the implementation of the Aesthetic Bot, an automated Twitter account that posts images of small game maps that are either user-made or generated from an evolutionary system.
1 code implementation • 27 Jun 2022 • Zehua Jiang, Sam Earle, Michael Cerny Green, Julian Togelius
Procedural Content Generation via Reinforcement Learning (PCGRL) foregoes the need for large human-authored data-sets and allows agents to train explicitly on functional constraints, using computable, user-defined measures of quality instead of target output.
no code implementations • 20 Jun 2022 • Ya-Chuan Hsu, Matthew C. Fontaine, Sam Earle, Maria Edwards, Julian Togelius, Stefanos Nikolaidis
To target specific diversity in the arrangements, we optimize the latent space of the GAN via a quality diversity algorithm to generate a diverse arrangement collection.
no code implementations • 11 Jun 2022 • Ahmed Khalifa, Michael Cerny Green, Julian Togelius
Search-based procedural content generation (PCG) is a well-known method for level generation in games.
1 code implementation • 28 Apr 2022 • Aaron Dharna, Charlie Summers, Rohin Dasari, Julian Togelius, Amy K. Hoover
This paper proposes a framework called Watts for implementing, comparing, and recombining open-ended learning (OEL) algorithms.
no code implementations • 11 Apr 2022 • Michael Cerny Green, Ahmed Khalifa, M Charity, Julian Togelius
In this paper, we present a method for automated persona-driven video game tutorial level generation.
no code implementations • 24 Mar 2022 • Michael Cerny Green, Ahmed Khalifa, M Charity, Debosmita Bhaumik, Julian Togelius
We investigate how to efficiently predict play personas based on playtraces.
no code implementations • 3 Mar 2022 • Aaron Dharna, Amy K Hoover, Julian Togelius, L. B. Soros
Furthermore, we analyze the impact of the minimal criterion on generated level diversity and inter-species transfer.
no code implementations • 21 Feb 2022 • Matthew Siper, Ahmed Khalifa, Julian Togelius
The Path of Destruction method, as we call it, views level generation as repair; levels are created by iteratively repairing from a random starting level.
1 code implementation • 8 Feb 2022 • Bryon Tjanaka, Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis
Training can then be viewed as a quality diversity (QD) optimization problem, where we search for a collection of performant policies that are diverse with respect to quantified behavior.
2 code implementations • 12 Sep 2021 • Sam Earle, Justin Snider, Matthew C. Fontaine, Stefanos Nikolaidis, Julian Togelius
We present a method of generating diverse collections of neural cellular automata (NCA) to design video game levels.
no code implementations • 11 Jul 2021 • Tae Jong Choi, Julian Togelius
Differential MAP-Elites is a novel algorithm that combines the illumination capacity of CVT-MAP-Elites with the continuous-space optimization capacity of Differential Evolution.
no code implementations • 5 Jul 2021 • Razieh Saremi, Hardik Yagnik, Julian Togelius, Ye Yang, Guenther Ruhe
In a competitive crowdsourcing marketplace, competition for shared worker resources from multiple simultaneously open tasks adds another layer of uncertainty to the potential outcomes of software crowdsourcing.
no code implementations • 17 May 2021 • Ruben Rodriguez-Torrado, Pablo Ruiz, Luis Cueto-Felgueroso, Michael Cerny Green, Tyler Friesen, Sebastien Matringe, Julian Togelius
PINNs are based on simple architectures, and learn the behavior of complex physical systems by optimizing the network parameters to minimize the residual of the underlying PDE.
1 code implementation • 6 May 2021 • Sam Earle, Maria Edwards, Ahmed Khalifa, Philip Bontrager, Julian Togelius
It has recently been shown that reinforcement learning can be used to train generators capable of producing high-quality game levels, with quality defined in terms of some user-specified heuristic.
no code implementations • 27 Mar 2021 • Christoph Salge, Michael Cerny Green, Rodrigo Canaan, Filip Skwarski, Rafael Fritsch, Adrian Brightmoore, Shaofang Ye, Changxing Cao, Julian Togelius
This article outlines what we learned from the first year of the AI Settlement Generation Competition in Minecraft, a competition about producing AI programs that can generate interesting settlements in Minecraft for an unseen map.
no code implementations • 22 Mar 2021 • Antonios Liapis, Hector P. Martinez, Julian Togelius, Georgios N. Yannakakis
DeLeNoX proceeds in alternating phases of exploration and transformation.
no code implementations • 20 Feb 2021 • Michael Cerny Green, Ahmed Khalifa, Philip Bontrager, Rodrigo Canaan, Julian Togelius
We present a new concept called Game Mechanic Alignment theory as a way to organize game mechanics through the lens of systemic rewards and agential motivations.
no code implementations • 3 Dec 2020 • Weiming Liu, Bin Li, Julian Togelius
Experimental results show that Neural ReCFR-B is competitive with the state-of-the-art neural CFR algorithms at a much lower training cost.
1 code implementation • 11 Nov 2020 • Chengpeng Hu, Ziqi Wang, Tianye Shu, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu
Our proposed technique is implemented with three state-of-the-art reinforcement learning algorithms and tested on the game set of the 2020 General Video Game AI Learning Competition.
1 code implementation • 13 Oct 2020 • Hejia Zhang, Matthew C. Fontaine, Amy K. Hoover, Julian Togelius, Bistra Dilkina, Stefanos Nikolaidis
Recent advancements in procedural content generation via machine learning enable the generation of video-game levels that are aesthetically similar to human-authored examples.
no code implementations • 9 Oct 2020 • Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios N. Yannakakis, Julian Togelius
This article surveys the various deep learning methods that have been applied to generate game content directly or indirectly, discusses deep learning methods that could be used for content generation purposes but are rarely used today, and envisages some limitations and potential future directions of deep learning for procedural content generation.
1 code implementation • 6 Aug 2020 • Omar Delarosa, Hang Dong, Mindy Ruan, Ahmed Khalifa, Julian Togelius
This paper introduces RL Brush, a level-editing tool for tile-based games designed for mixed-initiative co-creation.
1 code implementation • 16 Jul 2020 • Aaron Dharna, Julian Togelius, L. B. Soros
This paper introduces a POET-Inspired Neuroevolutionary System for KreativitY (PINSKY) in games, which co-generates levels for multiple video games and agents that play them.
1 code implementation • 11 Jul 2020 • Matthew C. Fontaine, Ruilin Liu, Ahmed Khalifa, Jignesh Modi, Julian Togelius, Amy K. Hoover, Stefanos Nikolaidis
Generative adversarial networks (GANs) are quickly becoming a ubiquitous approach to procedurally generating video game levels.
no code implementations • 1 Jun 2020 • Andre Mendes, Julian Togelius, Leandro dos Santos Coelho
In this work, we proposed a \textit{Multi-StaGe Transfer Learning} (MSGTL) approach that uses knowledge from simple classifiers trained in early stages to improve the performance of classifiers in the latter stages.
no code implementations • 26 May 2020 • Vanessa Volz, Niels Justesen, Sam Snodgrass, Sahar Asadi, Sami Purmonen, Christoffer Holmgård, Julian Togelius, Sebastian Risi
Recent procedural content generation via machine learning (PCGML) methods allow learning from existing content to produce similar content automatically.
1 code implementation • 17 May 2020 • Ahmed Khalifa, Julian Togelius
This paper introduces a new system to design constructive level generators by searching the space of constructive level generators defined by Marahel language.
1 code implementation • 28 Apr 2020 • Rodrigo Canaan, Xianbo Gao, Julian Togelius, Andy Nealen, Stefan Menzel
In this game, coordinated groups of players can leverage pre-established conventions to great effect, but playing in an ad-hoc setting requires agents to adapt to its partner's strategies with no previous coordination.
1 code implementation • 28 Apr 2020 • Rodrigo Canaan, Xianbo Gao, Youjin Chung, Julian Togelius, Andy Nealen, Stefan Menzel
Hanabi is a cooperative game that challenges exist-ing AI techniques due to its focus on modeling the mental states ofother players to interpret and predict their behavior.
1 code implementation • 3 Apr 2020 • Alberto Alvarez, Jose Font, Julian Togelius
We propose modeling designer style in mixed-initiative game content creation tools as archetypical design traces.
no code implementations • 15 Mar 2020 • Andre Mendes, Julian Togelius, Leandro dos Santos Coelho
We also introduce a sequence constraint in the output of an MLSSL classifier to guarantee the sequential pattern in the predictions.
no code implementations • 15 Mar 2020 • Andre Mendes, Julian Togelius, Leandro dos Santos Coelho
We present a novel framework that can combine multi-domain learning (MDL), data imputation (DI) and multi-task learning (MTL) to improve performance for classification and regression tasks in different domains.
1 code implementation • 6 Mar 2020 • Alberto Alvarez, Steve Dahlskog, Jose Font, Julian Togelius
We propose the Interactive Constrained MAP-Elites, a quality-diversity solution for game content generation, implemented as a new feature of the Evolutionary Dungeon Designer: a mixed-initiative co-creativity tool for designing dungeons.
1 code implementation • 12 Feb 2020 • Philip Bontrager, Julian Togelius
Unlike previous approaches to procedural content generation, Generative Playing Networks are end-to-end differentiable and do not require human-designed examples or domain knowledge.
no code implementations • 11 Feb 2020 • M Charity, Michael Cerny Green, Ahmed Khalifa, Julian Togelius
This paper introduces a fully automatic method of mechanic illumination for general video game level generation.
no code implementations • 7 Feb 2020 • Michael Cerny Green, Luvneesh Mugrai, Ahmed Khalifa, Julian Togelius
This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes" that contain specific mechanics, using mechanic-sequences from agent playthroughs as input specifications.
1 code implementation • 27 Jan 2020 • Chang Ye, Ahmed Khalifa, Philip Bontrager, Julian Togelius
Deep Reinforcement Learning (DRL) has shown impressive performance on domains with visual inputs, in particular various games.
6 code implementations • 24 Jan 2020 • Ahmed Khalifa, Philip Bontrager, Sam Earle, Julian Togelius
We investigate how reinforcement learning can be used to train level-designing agents.
6 code implementations • 5 Dec 2019 • Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis, Amy K. Hoover
Results from experiments based on standard continuous optimization benchmarks show that CMA-ME finds better-quality solutions than MAP-Elites; similarly, results on the strategic game Hearthstone show that CMA-ME finds both a higher overall quality and broader diversity of strategies than both CMA-ES and MAP-Elites.
no code implementations • 29 Nov 2019 • Sebastian Risi, Julian Togelius
Procedural Content Generation (PCG) refers to the practice, in videogames and other games, of generating content such as levels, quests, or characters algorithmically.
no code implementations • 3 Oct 2019 • Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green, Niels Justesen, Sebastian Risi, Julian Togelius
Theresults demonstrate that the new approach does not only gen-erate a larger number of levels that are playable but also gen-erates fewer duplicate levels compared to a standard GAN.
no code implementations • 6 Sep 2019 • Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Tiago Machado, Julian Togelius
In a user study, human-identified mechanics are compared against system-identified critical mechanics to verify alignment between humans and the system.
no code implementations • 13 Aug 2019 • Tiago Machado, Daniel Gopstein, Oded Nov, Angela Wang, Andy Nealen, Julian Togelius
Game development is a complex task involving multiple disciplines and technologies.
no code implementations • 12 Aug 2019 • Philip Bontrager, Ahmed Khalifa, Damien Anderson, Matthew Stephenson, Christoph Salge, Julian Togelius
Deep reinforcement learning has learned to play many games well, but failed on others.
no code implementations • 9 Aug 2019 • Tae Jong Choi, Julian Togelius, Yun-Gyung Cheong
A fast and efficient stochastic opposition-based learning (OBL) variant is proposed in this paper.
no code implementations • 15 Jul 2019 • Luvneesh Mugrai, Fernando De Mesentier Silva, Christoffer Holmgård, Julian Togelius
Matching tile games are an extremely popular game genre.
no code implementations • 15 Jul 2019 • Amy K. Hoover, Julian Togelius, Scott Lee, Fernando De Mesentier Silva
Games have benchmarked AI methods since the inception of the field, with classic board games such as Chess and Go recently leaving room for video games with related yet different sets of challenges.
1 code implementation • 9 Jul 2019 • Daniele Gravina, Ahmed Khalifa, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis
Quality-diversity (QD) algorithms search for a set of good solutions which cover a space as defined by behavior metrics.
no code implementations • 8 Jul 2019 • Tiago Machado, Dan Gopstein, Andy Nealen, Julian Togelius
In this paper, we introduce Pitako1, a tool that applies the Recommender System concept to assist humans in creative tasks.
no code implementations • 8 Jul 2019 • Rodrigo Canaan, Julian Togelius, Andy Nealen, Stefan Menzel
In complex scenarios where a model of other actors is necessary to predict and interpret their actions, it is often desirable that the model works well with a wide variety of previously unknown actors.
no code implementations • 2 Jul 2019 • Fernando de Mesentier Silva, Rodrigo Canaan, Scott Lee, Matthew C. Fontaine, Julian Togelius, Amy K. Hoover
Balancing an ever growing strategic game of high complexity, such as Hearthstone is a complex task.
no code implementations • 1 Jul 2019 • Tae Jong Choi, Julian Togelius, Yun-Gyung Cheong
The method monitors the results of each individual in the selection operator and performs the Cauchy mutation on consecutively failed individuals, which generates mutant vectors by perturbing the best individual with the Cauchy distribution.
no code implementations • 12 Jun 2019 • Ahmed Khalifa, Michael Cerny Green, Diego Perez-Liebana, Julian Togelius
We introduce the General Video Game Rule Generation problem, and the eponymous software framework which will be used in a new track of the General Video Game AI (GVGAI) competition.
no code implementations • 12 Jun 2019 • Alberto Alvarez, Steve Dahlskog, Jose Font, Julian Togelius
We propose the use of quality-diversity algorithms for mixed-initiative game content generation.
no code implementations • 11 Jun 2019 • Michael Cerny Green, Ahmed Khalifa, Athoug Alsoughayer, Divyesh Surana, Antonios Liapis, Julian Togelius
This paper presents a two-step generative approach for creating dungeons in the rogue-like puzzle game MiniDungeons 2.
no code implementations • 15 May 2019 • Ahmed Khalifa, Dan Gopstein, Julian Togelius
Elimination is a word puzzle game for browsers and mobile devices, where all levels are generated by a constrained evolutionary algorithm with no human intervention.
no code implementations • 14 May 2019 • Christoph Salge, Christian Guckelsberger, Michael Cerny Green, Rodrigo Canaan, Julian Togelius
We introduce the Chronicle Challenge as an optional addition to the Settlement Generation Challenge in Minecraft.
1 code implementation • 24 Apr 2019 • Matthew C. Fontaine, Scott Lee, L. B. Soros, Fernando De Mesentier Silva, Julian Togelius, Amy K. Hoover
Quality diversity (QD) algorithms such as MAP-Elites have emerged as a powerful alternative to traditional single-objective optimization methods.
1 code implementation • 18 Apr 2019 • Ahmed Khalifa, Michael Cerny Green, Gabriella Barros, Julian Togelius
The procedural generation of levels and content in video games is a challenging AI problem.
5 code implementations • 27 Mar 2019 • Debosmita Bhaumik, Ahmed Khalifa, Michael Cerny Green, Julian Togelius
We compare them on three different game level generation problems: Binary, Zelda, and Sokoban.
no code implementations • 17 Mar 2019 • Rodrigo Canaan, Christoph Salge, Julian Togelius, Andy Nealen
The extent to which these games benchmark consist of fair competition between human and AI is also a matter of debate.
no code implementations • 6 Mar 2019 • Marwan Mattar, Roozbeh Mottaghi, Julian Togelius, Danny Lange
This volume represents the accepted submissions from the AAAI-2019 Workshop on Games and Simulations for Artificial Intelligence held on January 29, 2019 in Honolulu, Hawaii, USA.
1 code implementation • 5 Feb 2019 • Kai Arulkumaran, Antoine Cully, Julian Togelius
In January 2019, DeepMind revealed AlphaStar to the world-the first artificial intelligence (AI) system to beat a professional player at the game of StarCraft II-representing a milestone in the progress of AI.
3 code implementations • 4 Feb 2019 • Arthur Juliani, Ahmed Khalifa, Vincent-Pierre Berges, Jonathan Harper, Ervin Teng, Hunter Henry, Adam Crespi, Julian Togelius, Danny Lange
Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment.
no code implementations • 28 Sep 2018 • Michael Cerny Green, Gabriella A. B. Barros, Antonios Liapis, Julian Togelius
This paper introduces DATA Agent, a system which creates murder mystery adventures from open data.
no code implementations • 26 Sep 2018 • Rodrigo Canaan, Haotian Shen, Ruben Rodriguez Torrado, Julian Togelius, Andy Nealen, Stefan Menzel
Hanabi is a cooperative card game with hidden information that has won important awards in the industry and received some recent academic attention.
no code implementations • 26 Sep 2018 • Rodrigo Canaan, Stefan Menzel, Julian Togelius, Andy Nealen
We propose the following question: what game-like interactive system would provide a good environment for measuring the impact and success of a co-creative, cooperative agent?
1 code implementation • 9 Sep 2018 • Matthew Stephenson, Damien Anderson, Ahmed Khalifa, John Levine, Jochen Renz, Julian Togelius, Christoph Salge
This paper introduces an information-theoretic method for selecting a subset of problems which gives the most information about a group of problem-solving algorithms.
1 code implementation • 18 Jul 2018 • Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Andy Nealen, Julian Togelius
The automatic generation of game tutorials is a challenging AI problem.
no code implementations • 11 Jul 2018 • Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Tiago Machado, Andy Nealen, Julian Togelius
This paper introduces a fully automatic method for generating video game tutorials.
1 code implementation • 28 Jun 2018 • Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, Sebastian Risi
However, when neural networks are trained in a fixed environment, such as a single level in a video game, they will usually overfit and fail to generalize to new levels.
no code implementations • 12 Jun 2018 • Ahmed Khalifa, Scott Lee, Andy Nealen, Julian Togelius
We describe a search-based approach to generating new levels for bullet hell games, which are action games characterized by and requiring avoidance of a very large amount of projectiles.
2 code implementations • 6 Jun 2018 • Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius, Jialin Liu, Diego Perez-Liebana
In this paper, we describe how we interface GVGAI to the OpenAI Gym environment, a widely used way of connecting agents to reinforcement learning problems.
no code implementations • 4 Jun 2018 • Christian Guckelsberger, Christoph Salge, Julian Togelius
Creating Non-Player Characters (NPCs) that can react robustly to unforeseen player behaviour or novel game content is difficult and time-consuming.
1 code implementation • 4 Jun 2018 • Giuseppe Cuccu, Julian Togelius, Philippe Cudre-Mauroux
Deep reinforcement learning, applied to vision-based problems like Atari games, maps pixels directly to actions; internally, the deep neural network bears the responsibility of both extracting useful information and making decisions based on it.
Ranked #21 on Atari Games on Atari 2600 Phoenix
no code implementations • 30 May 2018 • Gabriella A. B. Barros, Michael Cerny Green, Antonios Liapis, Julian Togelius
Maximalism in art refers to drawing on and combining multiple different sources for art creation, embracing the resulting collisions and heterogeneity.
no code implementations • 30 May 2018 • Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros, Julian Togelius
We propose the problem of tutorial generation for games, i. e. to generate tutorials which can teach players to play games, as an AI problem.
no code implementations • 27 Mar 2018 • Christoph Salge, Michael Cerny Green, Rodrigo Canaan, Julian Togelius
This paper introduces the settlement generation competition for Minecraft, the first part of the Generative Design in Minecraft challenge.
1 code implementation • 28 Feb 2018 • Diego Perez-Liebana, Jialin Liu, Ahmed Khalifa, Raluca D. Gaina, Julian Togelius, Simon M. Lucas
In 2014, The General Video Game AI (GVGAI) competition framework was created and released with the purpose of providing researchers a common open-source and easy to use platform for testing their AI methods with potentially infinity of games created using Video Game Description Language (VGDL).
no code implementations • 19 Feb 2018 • Christoffer Holmgård, Michael Cerny Green, Antonios Liapis, Julian Togelius
This paper describes a method for generative player modeling and its application to the automatic testing of game content using archetypal player models called procedural personas.
no code implementations • 14 Feb 2018 • Gabriella A. B. Barros, Michael Cerny Green, Antonios Liapis, Julian Togelius
This paper presents a framework for generating adventure games from open data.
no code implementations • 31 Jan 2018 • Damien Anderson, Matthew Stephenson, Julian Togelius, Christian Salge, John Levine, Jochen Renz
Deceptive games are games where the reward structure or other aspects of the game are designed to lead the agent away from a globally optimal policy.
1 code implementation • 24 Jan 2018 • Philip Bontrager, Wending Lin, Julian Togelius, Sebastian Risi
The main insight in this paper is that a GAN trained on a specific target domain can act as a compact and robust genotype-to-phenotype mapping (i. e. most produced phenotypes do resemble valid domain artifacts).
no code implementations • 25 Aug 2017 • Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi
In this article, we review recent Deep Learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games.
no code implementations • 12 Jul 2017 • Samuel Alvernaz, Julian Togelius
Neuroevolution has proven effective at many reinforcement learning tasks, but does not seem to scale well to high-dimensional controller representations, which are needed for tasks where the input is raw pixel data.
no code implementations • 21 May 2017 • Philip Bontrager, Aditi Roy, Julian Togelius, Nasir Memon, Arun Ross
The proposed method, referred to as Latent Variable Evolution, is based on training a Generative Adversarial Network on a set of real fingerprint images.
no code implementations • 9 May 2017 • Ahmed Khalifa, Gabriella A. B. Barros, Julian Togelius
DeepTingle is a text prediction and classification system trained on the collected works of the renowned fantastic gay erotica author Chuck Tingle.
no code implementations • 18 Mar 2017 • Jialin Liu, Julian Togelius, Diego Perez-Liebana, Simon M. Lucas
The space of possible parameter settings can be seen as a search space, and we can therefore use a Random Mutation Hill Climbing algorithm or other search methods to find the parameter settings that induce the best games.
no code implementations • 2 Feb 2017 • Adam Summerville, Sam Snodgrass, Matthew Guzdial, Christoffer Holmgård, Amy K. Hoover, Aaron Isaksen, Andy Nealen, Julian Togelius
This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content.
no code implementations • 6 Dec 2016 • Julian Togelius
If you are an artificial intelligence researcher, you should look to video games as ideal testbeds for the work you do.
1 code implementation • 27 Oct 2014 • Sebastian Risi, Julian Togelius
This paper surveys research on applying neuroevolution (NE) to games.
no code implementations • 5 Aug 2014 • Sebastian Risi, Jinhong Zhang, Rasmus Taarnby, Peter Greve, Jan Piskur, Antonios Liapis, Julian Togelius
It is clear that the current attempts at using algorithms to create artificial neural networks have had mixed success at best when it comes to creating large networks and/or complex behavior.
no code implementations • 10 Dec 2013 • Julian Togelius, Noor Shaker, Georgios N. Yannakakis
We further hypothesise that this form of curiosity is symmetric, and therefore that games that explore their players based on the principles of active learning will turn out to select game configurations that are interesting to the player that is being explored.
no code implementations • 6 Sep 2011 • Tom Schaul, Julian Togelius, Jürgen Schmidhuber
Artificial general intelligence (AGI) refers to research aimed at tackling the full problem of artificial intelligence, that is, create truly intelligent agents.