[PDF] Top 20 Deep Learning and Reinforcement Learning for Inventory Control
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Deep Learning and Reinforcement Learning for Inventory Control
... of inventory optimization, there is a number of research works based on a ...solve inventory optimization including a ...33 and 46 state ...average inventory cost. The results showed that ... Voir le document complet
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(Deep) Reinforcement learning for electric power system control and related problems: A short review and perspectives
... voltage control of a power ...[82] and the antijamming game frame- work for secure state estimation using multi-agent reinforcement learning to determine optimal path against an ... Voir le document complet
40
Reinforcement Learning for Electric Power System Decision and Control: Past Considerations and Perspectives
... the Deep RL field of research is revisiting some of the main works achieved in the past three decades using deep learning function approximators (see Busoniu et ...(2010) for a global view of ... Voir le document complet
10
Deep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling
... of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer ...per learning episode, and an in-house stabilized finite elements environment ... Voir le document complet
33
Deep reinforcement learning for the control of conjugate heat transfer
... of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer ...per learning episode, and an in-house stabilized finite elements environment ... Voir le document complet
33
Optimization and passive flow control using single-step deep reinforcement learning
... (one for the uncontrolled solution, one for the adjoint solution), so convergence would need to be achieved in less than two episodes (using single-step PPO) to match that ...inconvenient and very ... Voir le document complet
28
Deep reinforcement learning for the control of robotic manipulation: a focussed mini-review
... algorithm structure simple model multi-layer model model training time quick to train a model computationally intensive hardware requirement works with not powerful hardware high-performance computer Deep models ... Voir le document complet
13
Application of genetic algorithm and deep reinforcement learning for in-core fuel management
... hyperparameters for both GA and DQN, it was necessary to perform some hyperparameter ...values for each ...used for the sensitive hyperparameters to better explore the ...evaluated and ... Voir le document complet
21
Deep learning and reinforcement learning methods for grounded goal-oriented dialogue
... – for the questioner and oracle roles, and rewarded the questioner slightly more than the ...bonuses for making fewer ...other and players were banned after a certain number of ... Voir le document complet
164
Voronoi model learning for batch mode reinforcement learning
... Model learning–type RL Model learning–type reinforcement learning aims at solving optimal control problems by approximating the unknown functions f and ρ and solving the ... Voir le document complet
10
An Application of Deep Reinforcement Learning to Algorithmic Trading
... economists and traders who do not exploit ...following and mean reversion strategies, which are covered in detail in Chan (2009), Chan (2013) and Narang ...machine learning (ML) techniques in ... Voir le document complet
19
Deep Reinforcement Learning in Strategic Board Game Environments
... algorithm and a novel deep network archi- tecture to approximate the Q-function in strategic board game ...Q-value for each possible action is computed separately, as if it were the only possible ... Voir le document complet
18
Contributions to deep reinforcement learning and its applications in smartgrids
... approximator for the value function and/or the policy and/or the model is used, an asymptotic bias may appear because the policy cannot discriminate efficiently the different ...x-coordinate ... Voir le document complet
177
Learning to grow: control of material self-assembly using evolutionary reinforcement learning
... 3-gon and two 12-gons around each ...structure and so is a suitable order parameter for evolutionary ...target for self-assembly because its unit cell is large and must form from floppy ... Voir le document complet
14
Damping control by fusion of reinforcement learning and control Lyapunov functions
... proposed control schemes are ensured by design, ...available control choices to the RL ...basic control laws for the TCSC do not include any parameter, which is dependent on the network ... Voir le document complet
7
Multi-UAV Path Planning for Wireless Data Harvesting with Deep Reinforcement Learning
... meta- learning approach to control a group of drone base stations serving ground users with random uplink access ...small and obstruction- less environment, no maps are required in [14] and ... Voir le document complet
15
Real-Time Reinforcement Learning
... humans and artificial agents, it does not address the issue of turn-based interaction and the significance and consequences of the one-step ...continuous control with a single neural ... Voir le document complet
46
Linear-quadratic stochastic delayed control and deep learning resolution
... 4 Deep learning scheme 4.1 A quick reminder of PINNs and Deep Galerkin method for PDEs In order to solve ( ...(PINNs) and Deep Galerkin literatures, see Sirignano ... Voir le document complet
38
Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning
... through reinforcement learning – to offload the expensive online computation to an offline training ...by learning a value function that implicitly encodes cooperative ...of deep ... Voir le document complet
9
User-Adaptive Editing for 360 degree Video Streaming with Deep Reinforcement Learning
... to control the triggering of snap- changes, and to propose an architecture and a training framework to demo the ...sec.) and the future snap-changes already decided for the buffered seg- ... Voir le document complet
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