WSTypist is a new RL-based simulation model that reproduces human-like word suggestion strategies, individual differences, and adaptation to design changes in mobile text entry.
1998.Reinforcement learning: An introduction
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GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.
citing papers explorer
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Simulating Word Suggestion Usage in Mobile Typing to Guide Intelligent Text Entry Design
WSTypist is a new RL-based simulation model that reproduces human-like word suggestion strategies, individual differences, and adaptation to design changes in mobile text entry.
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On the Role of DAG topology in Energy-Aware Cloud Scheduling : A GNN-Based Deep Reinforcement Learning Approach
GNN-DRL cloud schedulers for DAG workflows degrade under topology shifts because structural mismatches disrupt message passing and policy generalization.