An attention-based DRL agent with Transformer encoder and GNN learns heuristics for qubit-to-core allocation in multi-core quantum systems to minimize state transfers and online compilation time.
Simple statistical gradient-following algorithms for connectionist reinforcement learning,
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A centralized HRL planner with HTAN, multi-stage curricula, and counterfactual baseline scales multi-robot task planning to 200 robots and 1000 racks on unlearned maps in RMFS.
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Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures
An attention-based DRL agent with Transformer encoder and GNN learns heuristics for qubit-to-core allocation in multi-core quantum systems to minimize state transfers and online compilation time.
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Scalable Hierarchical Reinforcement Learning for Hyper Scale Multi-Robot Task Planning
A centralized HRL planner with HTAN, multi-stage curricula, and counterfactual baseline scales multi-robot task planning to 200 robots and 1000 racks on unlearned maps in RMFS.