Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 32 for “"Atari"”.
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Single-player to Two-player Knowledge Transfer in Atari 2600 Games
… examines the proposed idea in ten different Atari 2600 environments using the Atari 2600 RAM as the input state. The advantages of using transfer learning from a single-player training process over training in a two-player setting from scratch are discussed, and the results are demonstrated …
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A resource guide to physical science/physics software for the Apple II, Atari, Pet, and TRS-80
… microcomputers: Apple II, Pet, TRS-80, and Atari. The resource guide will consist of the following: 1. A list and description of the high school physical science/physics software available for AISD teachers in the various Resource Centers. 2. A list and description of the commercial software …
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Efficient reinforcement learning through variance reduction and trajectory synthesis
… prove their effectiveness through experiments on Atari and MuJoCo environment.
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Cooperate to compete : composable planning and inference in multi-agent reinforcement learning
… models in two environments: a complex continuous Atari game Warlords and a grid-world stochastic game, and compare our model with human behavior.
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Addressing stale gradients in asynchronous federated deep reinforcement learning
… results from applying these methods to two Atari-2600 games demonstrate a relative speedup of up to 95\% compared to plain A3C in large and unstable federations.
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Beating the world's best at Super Smash Bros. with deep reinforcement learning
… intelligence. Many classes of RL tasks, from Atari games to motor control to board games, are now solvable by fairly generic algorithms, based on deep learning, that learn to play from experience with often minimal knowledge of the specific domain of interest. In this work, we will investigate …
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Inferring Structured World Models from Videos
… evaluate our inference performance on classical Atari games, as well as on physics-based mobile games.
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Design and evaluation of a hybrid multi-task learning model for optimizing deep reinforcement learning agents
… results obtained with OpenAI Gym library-based Atari 2600 video gaming environment demonstrate that the proposed hybrid multi-task learning model is successful in addressing key challenges associated with the performance optimization of deep reinforcement learning agents.
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Preferential proximal policy optimization in reinforcement learning
… value function. Empirical evaluations across six Atari environments demonstrate that our approach outperforms the baseline (vanilla PPO) across different tested environments, highlighting the value of our proposed method in learning complex environments.
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There Is Always an Option
… on both a custom Four-Room environment and Atari benchmarks, providing evidence that naturally occurring options can be identified in conventional deep RL agents. In addition, I develop interpretation methods based on $n$-gram statistics of action sequences and mean+variance spatial mappings …
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Self-supervised Representation Learning in Computer Vision and Reinforcement Learning
… alignment, and improves performance in most Atari environments. The second addresses the exploration problem. The method employs a world model of the SSL latent space, and the prediction error of this model indicates novel states required to explore. It shows strong performance on …
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Playing Tetris with deep reinforcement learning
… (DRL) has achieved outstanding performance with Atari and Go games. An initial attempt by Stevens and Pradhan (2016) to use deep reinforcement learning to play Tetris was unsuccessful. The objective of this thesis is to explore the potential of DRL with Tetris games. We started with a baseline …
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ACADIA: Efficient and Robust Adversarial Attacks Against Deep Reinforcement Learning
… and Proximal Policy Optimization (PPO), under Atari games and MuJoCo where both targeted and non-targeted attacks are considered with or without the state-of-the-art defenses in DRL (i.e., RADIAL and ATLA). Our results demonstrate that the proposed ACADIA outperforms existing gradient-based …
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Training and Inference in Early-Exit Deep Q-Networks for Efficient Reinforcement Learning
… input regimes: CartPole (vector state) and Atari Pong (pixels). Across both domains, EEDQN yields results that preserve baseline return while lowering expected per-decision FLOPs, with larger savings when many states are “easy” and confidently handled by the early exit. These results …
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Combining Functional and Automata Synthesis to Learn Causal Reactive Programs
… domain of causal mechanism discovery in Atari-style grid worlds, and develop a synthesis algorithm that infers a program describing the causal rules of the world from a sequence of observations. We evaluate our algorithm on two benchmark datasets, including one that we constructed using a …
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Evolutionary algorithms for optimising reinforcement learning policy approximation
… when training an agent that learns to play Atari Pong. The approach found models that were able to train reinforcement learning agents faster, and with fewer parameters than that found by OpenAI’s model in Blackwell et al. (2018) - a superhuman level of performance.
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Optimizing Verification of RTL Designs Using Reinforcement Learning Methods
… in the work by DeepMind Technologies to play Atari games. The RTL design used throughout the research is an LZW encoder as it is on one hand sufficiently complex to be representative, and on the other hand, it allows for an unambiguous assessment of the novel approach on the functional …
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Sequential decision making with feature-linear models
… exploration challenges and that it scales to the Atari Learning Environment, where it attains strong scores relative to competing methods.
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Universal artificial intelligence: evaluation and benchmarks
… Learning Environment (ALE) that integrates Atari 2600 games to test domain independent artificial agents. We will suggest practical ways to incorporate these features into the ALE platform to manage limitations of computing resources used to generate required environments for agents. The …
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Gaming the Network Poetic: Networking and Code in Art Games
… art games, such as those by Jason Rohrer and the Atari VCS games of Ian Bogost highlight experiments in a more focused use of the medium from concept to interaction, both between the player and the software but also foregrounding the code (both social codes and actual software) of the games. These …
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