Pages that link to "Item:Q2880944"

The following pages link to Transfer learning for reinforcement learning domains: a survey (Q2880944):

Displaying 50 items.

• Making friends on the fly: cooperating with new teammates (Q343919) (← links)
• Transfer of experience between reinforcement learning environments with progressive difficulty (Q703132) (← links)
• A transfer forecasting model for container throughput guided by discrete PSO (Q741894) (← links)
• Modeling of autonomous problem solving process by dynamic construction of task models in multiple tasks environment (Q853294) (← links)
• Transferring knowledge as heuristics in reinforcement learning: a case-based approach (Q898746) (← links)
• Transfer in variable-reward hierarchical reinforcement learning (Q1009300) (← links)
• Bayesian policy reuse (Q1689554) (← links)
• Overlapping layered learning (Q1690961) (← links)
• Preference-based reinforcement learning: a formal framework and a policy iteration algorithm (Q1945130) (← links)
• Progressive learning: a deep learning framework for continual learning (Q1982451) (← links)
• A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics (Q2021893) (← links)
• Phase portraits as movement primitives for fast humanoid robot control (Q2055044) (← links)
• POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition (Q2060079) (← links)
• Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning (Q2077963) (← links)
• Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning (Q2093367) (← links)
• Reinforcement learning: an industrial perspective (Q2094053) (← links)
• Task-specific loss: a teacher-centered approach to transfer learning between distinctly structured robotic agents (Q2101736) (← links)
• Transfer learning by mapping and revising boosted relational dependency networks (Q2203326) (← links)
• Reward is enough (Q2238710) (← links)
• Abstraction in data-sparse task transfer (Q2238727) (← links)
• Fast rates by transferring from auxiliary hypotheses (Q2361574) (← links)
• Optimal design of priors constrained by external predictors (Q2406909) (← links)
• Scalable transfer learning in heterogeneous, dynamic environments (Q2407414) (← links)
• Action-model acquisition for planning via transfer learning (Q2453728) (← links)
• Quantum classifiers for domain adaptation (Q2693860) (← links)
• Multi-fidelity reinforcement learning framework for shape optimization (Q2699352) (← links)
• Analysis on methods to effectively improve transfer learning performance (Q2699958) (← links)
• Bayesian reinforcement learning: a survey (Q2809805) (← links)
• A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems (Q3121512) (← links)
• Grounding Language for Transfer in Deep Reinforcement Learning (Q4611392) (← links)
• (Q4636987) (← links)
• A Hybrid Transfer Algorithm for Reinforcement Learning Based on Spectral Method (Q4926311) (← links)
• Visual transfer for reinforcement learning via gradient penalty based Wasserstein domain confusion (Q5088847) (← links)
• (Q5148970) (← links)
• (Q5159474) (← links)
• (Q5214215) (← links)
• A Gentle Introduction to Reinforcement Learning (Q5268414) (← links)
• Model-based Reinforcement Learning: A Survey (Q5870792) (← links)
• A Survey of Zero-shot Generalisation in Deep Reinforcement Learning (Q5881798) (← links)
• A Bayesian approach to (online) transfer learning: theory and algorithms (Q6066772) (← links)
• Embedding active learning in batch-to-batch optimization using reinforcement learning (Q6073100) (← links)
• Robust optimal well control using an adaptive multigrid reinforcement learning framework (Q6084341) (← links)
• A taxonomy for similarity metrics between Markov decision processes (Q6097106) (← links)
• Improving the efficiency of reinforcement learning for a spacecraft powered descent with Q-learning (Q6159476) (← links)
• Transferable dynamics models for efficient object-oriented reinforcement learning (Q6494370) (← links)
• Realizing self-adaptive systems via online reinforcement learning and feature-model-guided exploration (Q6536423) (← links)
• Exact learning dynamics of deep linear networks with prior knowledge (Q6539417) (← links)
• Inverse Kalman filtering problems for discrete-time systems (Q6546834) (← links)
• Reinforcement learning (Q6602227) (← links)
• Exact learning dynamics of deep linear networks with prior knowledge (Q6611437) (← links)