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reinforcement learning

What is Acceptably Safe for Reinforcement Learning?

What is Acceptably Safe for Reinforcement Learning?

... Machine Learning algorithms are becoming more prevalent in critical systems where dynamic decision making and efficiency are the ...of Reinforcement Learning in particu- lar, considering the ...

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Exploring Deep Reinforcement Learning with Multi Q Learning

Exploring Deep Reinforcement Learning with Multi Q Learning

... temporal-difference reinforcement learning algorithm which often explicitly stores state values using lookup ...Q- learning, achieving average returns up to ...

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Deep Reinforcement Learning for Swarm Systems

Deep Reinforcement Learning for Swarm Systems

... deep reinforcement learning for swarms: the high and possibly changing dimensionality of information perceived by each ...that learning embeddings end-to-end using neural network features scales well ...

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Paraphrase Generation with Deep Reinforcement Learning

Paraphrase Generation with Deep Reinforcement Learning

... in learning for paraphrasing ...Seq2Seq learning model with attention and copy mecha- nism (Bahdanau et ...inverse reinforcement learning (IRL) with outputs from the generator as supervisions ...

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Applications of deep learning and reinforcement learning to biological data

Applications of deep learning and reinforcement learning to biological data

... machine learning techniques. Overall, recent research in Deep learning (DL), Reinforcement learning (RL), and their combination (Deep RL) promise to revolutionize Artificial ...

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Sentence Simplification with Deep Reinforcement Learning

Sentence Simplification with Deep Reinforcement Learning

... a reinforcement learning framework (Williams, 1992): it explores the space of possible simplifications while learn- ing to maximize an expected reward function that encourages outputs which meet ...

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Practical Kernel-Based Reinforcement Learning

Practical Kernel-Based Reinforcement Learning

... of reinforcement learning (Sch¨ olkopf and Smola, ...of reinforcement learning is to “kernelize” some formulation of the value-function approximation problem (Xu et ...to reinforcement ...

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Deep Reinforcement Learning for Dialogue Generation

Deep Reinforcement Learning for Dialogue Generation

... of reinforcement learning, which have been widely ap- plied in MDP and POMDP dialogue systems (see Re- lated Work section for ...ral reinforcement learning (RL) generation method, which can ...

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Learning to Teach in Cooperative Multiagent Reinforcement Learning

Learning to Teach in Cooperative Multiagent Reinforcement Learning

... inverse reinforcement learning (Ng and Russell 2000), apprenticeship learning (Abbeel and Ng 2004), and learning from demonstration (Argall et ...curriculum learning (Bengio et ...

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Reinforcement Learning for Generative Art

Reinforcement Learning for Generative Art

... To better engage with RL-based generative art, the dissertation creates RL5, a JavaScript library built on top of p5.js to improve the accessibility of reinforcement learning for creatives. RL5 allows ...

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Collaborative reinforcement learning of autonomic behaviour

Collaborative reinforcement learning of autonomic behaviour

... Collaborative Reinforcement Learning (CRL) is a bottom-up approach to tackling the complex time- varying problems of engineering autonomic behaviour for distributed systems where there is no support for ...

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Neural Logic Reinforcement Learning

Neural Logic Reinforcement Learning

... Deep reinforcement learning (DRL) has achieved significant breakthroughs in various ...Logic Reinforcement Learning (NLRL) to represent the policies in reinforcement learning by ...

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Evolutionary Function Approximation for Reinforcement Learning

Evolutionary Function Approximation for Reinforcement Learning

... dressing reinforcement learning problems. In most real-world reinforcement learning tasks, TD methods require a function approximator to represent the value ...standard reinforcement ...

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Lyapunov Design for Safe Reinforcement Learning

Lyapunov Design for Safe Reinforcement Learning

... reliable reinforcement learning agents based on Lyapunov design ...any reinforcement learning algorithm and at all times, including while the agent is learning and taking exploratory ...

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Active Bayesian perception and reinforcement learning

Active Bayesian perception and reinforcement learning

... ment learning is tested with a simple but illustrative task of perceiving object curvature using tapping movements of a biomimetic fingertip with unknown contact location ...standard reinforcement ...

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Reinforcement Learning with Factored States and Actions

Reinforcement Learning with Factored States and Actions

... are learning “macro” or “basis” ...during reinforcement learning, we find a set that can form useful actions, while excluding action combinations that are either not seen or not ...

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Determinantal Reinforcement Learning

Determinantal Reinforcement Learning

... A DPP defines a probability distribution over the subsets from a ground set. The probability of a subset is propor- tional to the determinant of a principal submatrix of a posi- tive semidefinite matrix, where the ...

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Hierarchical Average Reward Reinforcement Learning

Hierarchical Average Reward Reinforcement Learning

... Reinforcement learning (RL) is a machine learning framework for solving sequential decision- making problems. Despite its successes in a number of different domains, including backgammon (Tesauro, ...

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Self reflective deep reinforcement learning

Self reflective deep reinforcement learning

... On-line reinforcement learning agents is difficult to train. It takes long to train because the agent does not have direct answer to the input in hand, it has to rely on own assessment of how good or bad ...

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Construction of Approximation Spaces for Reinforcement Learning

Construction of Approximation Spaces for Reinforcement Learning

... Reinforcement learning (RL, Sutton and Barto, 1998; Bertsekas and Tsitsiklis, 1996) provides a framework to autonomously learn control policies in stochastic environments and has become pop- ular in recent ...

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