Essays about: "A3C"
Found 5 essays containing the word A3C.
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1. Asynchronous Advantage Actor-Critic and Flappy Bird
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Games provide ideal environments for assessingreinforcement learning algorithms because of their simple dynamicsand their inexpensive testing, compared to real-worldenvironments. Asynchronous Advantage Actor-Critic (A3C), developedby DeepMind, has shown significant improvements inperformance over other state-of-the-art algorithms on Atarigames. READ MORE
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2. A scalable species-based genetic algorithm for reinforcement learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Existing methods in Reinforcement Learning (RL) that rely on gradient estimates suffer from the slow rate of convergence, poor sample efficiency, and computationally expensive training, especially when dealing with complex real-world problems with a sizable dimensionality of the state and action space. In this work, we attempt to leverage the benefits of evolutionary computation as a competitive, scalable, and gradient-free alternative to training deep neural networks for RL-specific problems. READ MORE
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3. Mixing Music Using Deep Reinforcement Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep Reinforcement Learning has recently seen good results in tasks such as board games, computer games and the control of autonomous vehicles. Stateof-the-art autonomous DJ-systems generating mixed audio hard-code the mixing strategy commonly with a cross-fade transition. READ MORE
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4. Exploring Deep Reinforcement Learning Algorithms for Homogeneous Multi-Agent Systems
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Despite advances in Deep Reinforcement Learning, multi-agent systems remain somewhat unexplored, in comparison to single-agent systems, with few clear conclusions. In order to investigate this, two algorithms have been implemented and tested on a simple multi-agent system: Deep Q Learning with several improvements (EDQN) and Asynchronous Advantage ActorCritic (A3C). READ MORE
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5. Asynchronous Advantage Actor-Critic with Adam Optimization and a Layer Normalized Recurrent Network
University essay from KTH/Optimeringslära och systemteoriAbstract : State-of-the-art deep reinforcement learning models rely on asynchronous training using multiple learner agents and their collective updates to a central neural network. In this thesis, one of the most recent asynchronous policy gradientbased reinforcement learning methods, i.e. READ MORE
