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Journal articles on the topic 'Atari Video Games'

Author: Grafiati

Published: 4 June 2021

Last updated: 27 July 2025

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1

Zhang, Ruohan, Calen Walshe, Zhuode Liu, et al. "Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 6811–20. http://dx.doi.org/10.1609/aaai.v34i04.6161.

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Large-scale public datasets have been shown to benefit research in multiple areas of modern artificial intelligence. For decision-making research that requires human data, high-quality datasets serve as important benchmarks to facilitate the development of new methods by providing a common reproducible standard. Many human decision-making tasks require visual attention to obtain high levels of performance. Therefore, measuring eye movements can provide a rich source of information about the strategies that humans use to solve decision-making tasks. Here, we provide a large-scale, high-quality

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Geffner, Tomas, and Hector Geffner. "Width-Based Planning for General Video-Game Playing." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 11, no. 1 (2021): 23–29. http://dx.doi.org/10.1609/aiide.v11i1.12786.

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IW(1) is a simple search algorithm that assumes that states can be characterized in terms of a set of boolean features or atoms. IW(1) consists of a standard breadth-first search with one variation: a newly generated state is pruned if it does not make a new atom true. Thus, while a breadth-first search runs in time that is exponential in the number of atoms, IW(1) runs in linear time. Variations of the algorithm have been shown to yield state-of-the-art results in classical planning and more recently in the Atari video games. In this paper, we use the algorithm for selecting actions in the ga

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Nyitray, Kristen J. "The Alert Collector: Game On to Game After: Sources for Video Game History." Reference & User Services Quarterly 59, no. 1 (2019): 7. http://dx.doi.org/10.5860/rusq.59.1.7219.

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Kristen Nyitray began her immersion in video games with an Atari 2600 and ColecoVision console and checking out games from her local public library. Later in life, she had the opportunity to start building a video game studies collection in her professional career as an archivist and special collections librarian. While that project has since ended, you get the benefit of her expansive knowledge of video game sources in “Game On to Game After: Sources for Video Game History.” There is much in this column to help librarians wanting to support research in this important entertainment form. Ready

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Reinhard, Andrew. "Excavating Atari: Where the Media was the Archaeology." Journal of Contemporary Archaeology 2, no. 1 (2015): 86–93. https://doi.org/10.1558/jca.v2i1.27108.

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A team of archaeologists excavated Alamogordo, New Mexico’s famed “Atari Burial Ground” in 2014 to media fanfare and public speculation of what archaeology is. This salvage project was the first archaeological dig of an assemblage of video games, in this case thousands of Atari cartridges buried by the company in 1983, quickly becoming the stuff of urban legend. Filmed by documentarians for Microsoft’s Xbox Live, the dig marked a global confluence of science, spectacle, and social media, a literal archaeology of media.

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Williams, Deborah A., and Jack O. Jenkins. "Role of Competitive Anxiety in the Performance of Black College Basketball Players." Perceptual and Motor Skills 63, no. 2 (1986): 847–53. http://dx.doi.org/10.2466/pms.1986.63.2.847.

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Scores on an Atari video game, Martens's Competitive Anxiety Scale and Life Experience Survey, and coaches' ratings of actual performance over 10 home basketball games were obtained for 8 black players and 7 black controls. Several significant ( p ≤ .01) correlations of anxiety and performance with stress were low to moderate and encourage a full-scale study with a larger sample and standardized measures.

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Köster, Raphael, and Martin J. Chadwick. "What can classic Atari video games tell us about the human brain?" Neuron 109, no. 4 (2021): 568–70. http://dx.doi.org/10.1016/j.neuron.2021.01.021.

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Widendaële, Arnaud. "Michael Z. Newman, Atari Age. The Emergence of Video Games in America." 1895, no. 86 (December 1, 2018): 193–96. http://dx.doi.org/10.4000/1895.7192.

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Moretti, Myrna. "Keeping Up With Atari: Neoliberal Expectations in Early Electronics Advertising." TMG Journal for Media History 26, no. 2 (2023): 1–22. http://dx.doi.org/10.18146/tmg.847.

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During the early 1980s, ad campaigns framed purchasing and using emerging consumer electronics as tools for accessing, what Lauren Berlant called, ‘the good life.’ Computers, video games, VCRs, and cassette players might help consumers cultivate a neoliberal, upwardly mobile, and implicitly white, lifestyle. This paper explores early personal computer and home console video game advertisements as a cultural discourse that framed emerging technology through normative gendered, raced, and classed everyday lifestyles in an American context. The central case study is the early 1980s televisual ad

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O'Donnell, Casey. "Atari Age: The Emergence of Video Games in America by Michael Z. Newman." Technology and Culture 63, no. 4 (2022): 1214–15. http://dx.doi.org/10.1353/tech.2022.0172.

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Lin, Jhang, Lee, Lin, and Young. "Using a Reinforcement Q-Learning-Based Deep Neural Network for Playing Video Games." Electronics 8, no. 10 (2019): 1128. http://dx.doi.org/10.3390/electronics8101128.

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This study proposed a reinforcement Q-learning-based deep neural network (RQDNN) that combined a deep principal component analysis network (DPCANet) and Q-learning to determine a playing strategy for video games. Video game images were used as the inputs. The proposed DPCANet was used to initialize the parameters of the convolution kernel and capture the image features automatically. It performs as a deep neural network and requires less computational complexity than traditional convolution neural networks. A reinforcement Q-learning method was used to implement a strategy for playing the vide

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Dharna, Aaron, Julian Togelius, and L. B. Soros. "Co-Generation of Game Levels and Game-Playing Agents." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 16, no. 1 (2020): 203–9. http://dx.doi.org/10.1609/aiide.v16i1.7431.

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Open-endedness, a longstanding cornerstone of artificial life research, is the ability of systems to generate potentially unbounded ontologies of increasing novelty and complexity. Engineering generative systems displaying at least some degree of this ability is a goal with clear applications to procedural content generation in games. The Paired Open-Ended Trailblazer (POET) algorithm, heretofore explored only in a biped walking domain, is a coevolutionary system that simultaneously generates environments and agents that can solve them. This paper introduces a POET-Inspired Neuroevolutionary S

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COLLINS, KAREN. "In the Loop: Creativity and Constraint in 8-bit Video Game Audio." Twentieth-Century Music 4, no. 2 (2007): 209–27. http://dx.doi.org/10.1017/s1478572208000510.

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AbstractThis article explores the sound capabilities of video game consoles of the 8-bit era (c.1975–85) in order to discuss the impact that technological constraints had on shaping aesthetic decisions in the composition of music for the early generation of games. Comparing examples from the Commodore 64 (C64), the Nintendo Entertainment System (NES), the Atari VCS, and the arcade consoles, I examine various approaches and responses (in particular the use of looping) to similar technological problems, and illustrate how these responses are as much a decision made by the composer as a matter of

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Crooks, Roderic. "Atari Age: The Emergence of Video Games in America by Michael Z. Newman (review)." Information & Culture 53, no. 3-4 (2018): 372–74. https://doi.org/10.1353/lac.2018.0015.

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JYOTHIRADITYA PERI. "Video gaming industry in the US." International Journal of Science and Research Archive 11, no. 1 (2024): 1257–65. http://dx.doi.org/10.30574/ijsra.2024.11.1.0194.

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Generations after generations, the entertainment industry evolved multiple folds, be it music, be it movies, be it sports, be it video games. Each industry doesn’t only set trends each decade but also changes peoples’ lifestyle. Video games are something which is involved almost in every person’s life. Some people play them when they’re young, some play in their teens, some play after they come home from office and some play after they retire. The video games were simply designed simulations that was started in 1950’s and 1960’s by computer scientists on the early computers. In 1952, British p

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Hu, Yueyue, Shiliang Sun, Xin Xu, and Jing Zhao. "Multi-View Deep Attention Network for Reinforcement Learning (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (2020): 13811–12. http://dx.doi.org/10.1609/aaai.v34i10.7177.

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The representation approximated by a single deep network is usually limited for reinforcement learning agents. We propose a novel multi-view deep attention network (MvDAN), which introduces multi-view representation learning into the reinforcement learning task for the first time. The proposed model approximates a set of strategies from multiple representations and combines these strategies based on attention mechanisms to provide a comprehensive strategy for a single-agent. Experimental results on eight Atari video games show that the MvDAN has effective competitive performance than single-vi

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Barr, Matthew. "The Force Is Strong with This One (but Not That One): What Makes a Successful Star Wars Video Game Adaptation?" Arts 9, no. 4 (2020): 131. http://dx.doi.org/10.3390/arts9040131.

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The Star Wars films have probably spawned more video game adaptations than any other franchise. From the 1982 release of The Empire Strikes Back on the Atari 2600 to 2019’s Jedi: Fallen Order, around one hundred officially licensed Star Wars games have been published to date. Inevitably, the quality of these adaptations has varied, ranging from timeless classics such as Star Wars: Knights of the Old Republic, to such lamentable cash grabs as the Attack of the Clones movie tie-in. But what makes certain ludic adaptations of George Lucas’ space opera more successful than others? To answer this q

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Lawlor, Shannon. "Book Review: Atari Age: The Emergence of Video Games in America, by Michael Z. Newman." Television & New Media 20, no. 3 (2018): 311–13. http://dx.doi.org/10.1177/1527476418784657.

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Gawade, Udayraj Sambhaji. "Retro-Plus Portable Gaming Console." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34880.

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The Indian E-sports gaming industry is burgeoning, with a market value of nearly 2000 crores and rapid expansion. This growth primarily targets the younger generation's preference for high-priced online games that necessitate a sophisticated gaming setup. Introducing the Retro-Plus Portable Gaming Console, a compact pocket-sized device enabling players to enjoy classic 90s video games without the need for internet connectivity or elaborate configurations. Amidst the resurgence of retro gaming, we explore a cost-effective alternative by harnessing the power of Raspberry Pi boards equipped with

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Vellala, Sri Sai Akhil, Sagar Velpula, Meera Alphy Dr., and K. Shirisha Ms. "Ball Pong Game." Research and Applications of Web Development and Design 7, no. 3 (2024): 23–27. https://doi.org/10.5281/zenodo.12754365.

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<em>The Pong game, a pioneer in the world of video gaming, is a simple yet engaging two- dimensional sports game that simulates table tennis. Created by Atari in the early 1970s, Pong is widely regarded as one of the first video games to gain mainstream popularity. Developing a Pong game using Java provides an excellent opportunity to delve into fundamental game development concepts while leveraging the capabilities of Java's versatile programming environment. The development process will involve designing and implementing the game logic, creating graphical assets for the user interface, and t

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Ulu, Eren, Tolga Capin, Bora Çelikkale, and Ufuk Celikcan. "Task-Based Visual Attention for Continually Improving the Performance of Autonomous Game Agents." Electronics 12, no. 21 (2023): 4405. http://dx.doi.org/10.3390/electronics12214405.

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Deep Reinforcement Learning (DRL) has been effectively performed in various complex environments, such as playing video games. In many game environments, DeepMind’s baseline Deep Q-Network (DQN) game agents performed at a level comparable to that of humans. However, these DRL models require many experience samples to learn and lack the adaptability to changes in the environment and handling complexity. In this study, we propose Attention-Augmented Deep Q-Network (AADQN) by incorporating a combined top-down and bottom-up attention mechanism into the DQN game agent to highlight task-relevant fea

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Jiang, Ray, Shangtong Zhang, Veronica Chelu, Adam White, and Hado van Hasselt. "Learning Expected Emphatic Traces for Deep RL." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 7015–23. http://dx.doi.org/10.1609/aaai.v36i6.20660.

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Off-policy sampling and experience replay are key for improving sample efficiency and scaling model-free temporal difference learning methods. When combined with function approximation, such as neural networks, this combination is known as the deadly triad and is potentially unstable. Recently, it has been shown that stability and good performance at scale can be achieved by combining emphatic weightings and multi-step updates. This approach, however, is generally limited to sampling complete trajectories in order, to compute the required emphatic weighting. In this paper we investigate how to

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Das, Ria, Joshua B. Tenenbaum, Armando Solar-Lezama, and Zenna Tavares. "Combining Functional and Automata Synthesis to Discover Causal Reactive Programs." Proceedings of the ACM on Programming Languages 7, POPL (2023): 1628–58. http://dx.doi.org/10.1145/3571249.

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We present a new algorithm that synthesizes functional reactive programs from observation data. The key novelty is to iterate between a functional synthesis step, which attempts to generate a transition function over observed states, and an automata synthesis step, which adds any additional latent state necessary to fully account for the observations. We develop a functional reactive DSL called Autumn that can express a rich variety of causal dynamics in time-varying, Atari-style grid worlds, and apply our method to synthesize Autumn programs from data. We evaluate our algorithm on a benchmark

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Kelly, Stephen, and Malcolm I. Heywood. "Emergent Solutions to High-Dimensional Multitask Reinforcement Learning." Evolutionary Computation 26, no. 3 (2018): 347–80. http://dx.doi.org/10.1162/evco_a_00232.

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Algorithms that learn through environmental interaction and delayed rewards, or reinforcement learning (RL), increasingly face the challenge of scaling to dynamic, high-dimensional, and partially observable environments. Significant attention is being paid to frameworks from deep learning, which scale to high-dimensional data by decomposing the task through multilayered neural networks. While effective, the representation is complex and computationally demanding. In this work, we propose a framework based on genetic programming which adaptively complexifies policies through interaction with th

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Sherstan, Craig, Shibhansh Dohare, James MacGlashan, Johannes Günther, and Patrick M. Pilarski. "Gamma-Nets: Generalizing Value Estimation over Timescale." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 5717–25. http://dx.doi.org/10.1609/aaai.v34i04.6027.

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Temporal abstraction is a key requirement for agents making decisions over long time horizons—a fundamental challenge in reinforcement learning. There are many reasons why value estimates at multiple timescales might be useful; recent work has shown that value estimates at different time scales can be the basis for creating more advanced discounting functions and for driving representation learning. Further, predictions at many different timescales serve to broaden an agent's model of its environment. One predictive approach of interest within an online learning setting is general value functi

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Pham, Son, Keyi Zhang, Tung Phan, Jasper Ding, and Christopher Dancy. "Playing SNES Games With NeuroEvolution of Augmenting Topologies." Proceedings of the AAAI Conference on Artificial Intelligence 32, no. 1 (2018). http://dx.doi.org/10.1609/aaai.v32i1.12199.

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Teaching a computer to play video games has generally been seen as a reasonable benchmark for developing new AI techniques. In recent years, extensive research has been completed to develop reinforcement learning (RL) algorithms to play various Atari 2600 games, resulting in new applications of algorithms such as Deep Q-Learning or Policy Gradient that outperform humans. However, games from Super Nintendo Entertainment System (SNES) are far more complicated than Atari 2600 games as many of these state-of-the-art algorithms still struggle to perform on this platform. In this paper, we present a

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Shein, James B., and Judith Crown. "Atari: Between a Rock and a Hard Place." Kellogg School of Management Cases, January 20, 2017, 1–11. http://dx.doi.org/10.1108/case.kellogg.2016.000030.

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Atari, a maker of video games, went through several owners over the years winding up controlled by Infogrames, a French publisher of video games. Infogrames later sold Atari shares in a secondary public offering, eventually reducing the parent’s share to 51.6 percent by September 2005 creating a complicated two-tier ownership structure. Two levels of management made it difficult to get things done. The financial structure was a problem for Infogrames because the French company had to consolidate 100 percent of Atari’s results even though it only owned 51 percent of the company. Atari was gener

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Fleury, James. "From Superman to Swordquest: Atari and early video game labor exploitation." American Journal of Economics and Sociology, November 6, 2023. http://dx.doi.org/10.1111/ajes.12551.

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AbstractUnionization efforts have only recently begun to address the exploitative conditions of working in video games. Despite such conditions dating back to the industry's origins, scholarship has tended to focus on contemporary labor issues over those of the past. To illustrate early forms of video game exploitation, I examine the history of industry pioneer Atari under the ownership of media conglomerate Warner Communications, Inc. (WCI) from 1976 to 1984. Soon after acquiring Atari, WCI installed a new CEO and pursued convergence initiatives. As a corporate ideal, convergence implies two

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Gulrez, Tauseef, and Warren Mansell. "High Performance on Atari Games Using Perceptual Control Architecture Without Training." Journal of Intelligent & Robotic Systems 106, no. 2 (2022). http://dx.doi.org/10.1007/s10846-022-01747-5.

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AbstractDeep reinforcement learning (DRL) requires large samples and a long training time to operate optimally. Yet humans rarely require long periods of training to perform well on novel tasks, such as computer games, once they are provided with an accurate program of instructions. We used perceptual control theory (PCT) to construct a simple closed-loop model which requires no training samples and training time within a video game study using the Arcade Learning Environment (ALE). The model was programmed to parse inputs from the environment into hierarchically organised perceptual signals,

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Švelch, Jan. "Developer Credit: Para-Industrial Hierarchies of In-Game Credit Attribution in the Video Game Industry." Games and Culture, July 29, 2021, 155541202110344. http://dx.doi.org/10.1177/15554120211034408.

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Developer credit has been a contested issue in the video game industry since the 1970–80s, when Atari prevented its programmers from publicly claiming authorship for games they had developed. The negotiations over what constitutes a noteworthy contribution to video game development are ongoing and play out in the unregulated space of in-game credits. Here, some creators get top billing akin to film and television credits, while others struggle to be recognized for their work. By analyzing in-game credits of 100 contemporary games published between 2016 and 2020 and representing four major sect

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Braylan, Alexander, Mark Hollenbeck, Elliot Meyerson, and Risto Miikkulainen. "Reuse of Neural Modules for General Video Game Playing." Proceedings of the AAAI Conference on Artificial Intelligence 30, no. 1 (2016). http://dx.doi.org/10.1609/aaai.v30i1.10014.

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A general approach to knowledge transfer is introduced in which an agent controlled by a neural network adapts how it reuses existing networks as it learns in a new domain. Networks trained for a new domain can improve their performance by routing activation selectively through previously learned neural structure, regardless of how or for what it was learned. A neuroevolution implementation of this approach is presented with application to high-dimensional sequential decision-making domains. This approach is more general than previous approaches to neural transfer for reinforcement learning. I

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Xu, Ruiyang, and Karl Lieberherr. "Learning self-play agents for combinatorial optimization problems." Knowledge Engineering Review 35 (2020). http://dx.doi.org/10.1017/s026988892000020x.

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Abstract Recent progress in reinforcement learning (RL) using self-play has shown remarkable performance with several board games (e.g., Chess and Go) and video games (e.g., Atari games and Dota2). It is plausible to hypothesize that RL, starting from zero knowledge, might be able to gradually approach a winning strategy after a certain amount of training. In this paper, we explore neural Monte Carlo Tree Search (neural MCTS), an RL algorithm that has been applied successfully by DeepMind to play Go and Chess at a superhuman level. We try to leverage the computational power of neural MCTS to s

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Browsh, Jared Bahir. "Review of Atari Age: The Emergence of Video Games in America by Michael Z. Newman (MIT Press)." Lateral 6, no. 2 (2017). http://dx.doi.org/10.25158/l6.2.14.

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Veness, Joel, Marc Bellemare, Marcus Hutter, Alvin Chua, and Guillaume Desjardins. "Compress and Control." Proceedings of the AAAI Conference on Artificial Intelligence 29, no. 1 (2015). http://dx.doi.org/10.1609/aaai.v29i1.9600.

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This paper describes a new information-theoretic policy evaluation technique for reinforcement learning. This technique converts any compression or density model into a corresponding estimate of value. Under appropriate stationarity and ergodicity conditions, we show that the use of a sufficiently powerful model gives rise to a consistent value function estimator. We also study the behavior of this technique when applied to various Atari 2600 video games, where the use of suboptimal modeling techniques is unavoidable. We consider three fundamentally different models, all too limited to perfect

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Lipovetzky, Nir, and Hector Geffner. "Best-First Width Search: Exploration and Exploitation in Classical Planning." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 1 (2017). http://dx.doi.org/10.1609/aaai.v31i1.11027.

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It has been shown recently that the performance of greedy best-first search (GBFS) for computing plans that are not necessarily optimal can be improved by adding forms of exploration when reaching heuristic plateaus: from random walks to local GBFS searches. In this work, we address this problem but using structural exploration methods resulting from the ideas of width-based search. Width-based methodsseek novel states, are not goal oriented, and their power has been shown recently in the Atari and GVG-AI video-games. We show first that width-based exploration in GBFS is more effective than GB

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Bougie, Nicolas, and Ryutaro Ichise. "Hierarchical learning from human preferences and curiosity." Applied Intelligence, September 28, 2021. http://dx.doi.org/10.1007/s10489-021-02726-3.

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AbstractRecent success in scaling deep reinforcement algorithms (DRL) to complex problems has been driven by well-designed extrinsic rewards, which limits their applicability to many real-world tasks where rewards are naturally extremely sparse. One solution to this problem is to introduce human guidance to drive the agent’s learning. Although low-level demonstrations is a promising approach, it was shown that such guidance may be difficult for experts to demonstrate since some tasks require a large amount of high-quality demonstrations. In this work, we explore human guidance in the form of h

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A.Wilson, Jason. "Performance, anxiety." M/C Journal 5, no. 2 (2002). http://dx.doi.org/10.5204/mcj.1952.

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In a recent gaming anthology, Henry Jenkins cannot help contrasting his son's cramped, urban, media-saturated existence with his own idyllic, semi-rural childhood. After describing his own Huck Finn meanderings over "the spaces of my boyhood" including the imaginary kingdoms of Jungleoca and Freedonia, Jenkins relates his version of his son's experiences: My son, Henry, now 16 has never had a backyard He has grown up in various apartment complexes, surrounded by asphalt parking lots with, perhaps, a small grass buffer from the street… Once or twice, when I became exasperated by my son's consta

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Flynn, Bernadette. "Towards an Aesthetics of Navigation." M/C Journal 3, no. 5 (2000). http://dx.doi.org/10.5204/mcj.1875.

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Introduction Explorations of the multimedia game format within cultural studies have been broadly approached from two perspectives: one -- the impact of technologies on user interaction particularly with regard to social implications, and the other -- human computer interactions within the framework of cybercultures. Another approach to understanding or speaking about games within cultural studies is to focus on the game experience as cultural practice -- as an activity or an event. In this article I wish to initiate an exploration of the aesthetics of player space as a distinctive element of

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Wasser, Frederick. "Media Is Driving Work." M/C Journal 4, no. 5 (2001). http://dx.doi.org/10.5204/mcj.1935.

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My thesis is that new media, starting with analog broadcast and going through digital convergence, blur the line between work time and free time. The technology that we are adopting has transformed free time into potential and actual labour time. At the dawn of the modern age, work shifted from tasked time to measured time. Previously, tasked time intermingled work and leisure according to the vagaries of nature. All this was banished when industrial capitalism instituted the work clock (Mumford 12-8). But now, many have noticed how post-industrial capitalism features a new intermingling captu

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Chesher, Chris. "Mining Robotics and Media Change." M/C Journal 16, no. 2 (2013). http://dx.doi.org/10.5204/mcj.626.

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Introduction Almost all industries in Australia today have adopted digital media in some way. However, uses in large scale activities such as mining may seem to be different from others. This article looks at mining practices with a media studies approach, and concludes that, just as many other industries, mining and media have converged. Many Australian mine sites are adopting new media for communication and control to manage communication, explore for ore bodies, simulate forces, automate drilling, keep records, and make transport and command robotic. Beyond sharing similar digital devices f

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