Greedy
PulseAugur coverage of Greedy — every cluster mentioning Greedy across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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LLM decoding strategies: Greedy, Beam Search, Sampling, Top-K, and Top-P explained
Language models generate text by turning probability distributions into sequences of tokens, with different decoding strategies leading to varied outputs. Greedy decoding selects the most probable token at each step, wh…
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New DRL Framework Optimizes Urban EV Fleet Control
Researchers have developed a new framework for controlling urban electric vehicle (EV) fleets that uses distributionally robust reinforcement learning (DRL) to handle uncertain demand and travel times. This approach, ca…
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New 'Delight-gated exploration' algorithm optimizes vast action spaces
Researchers have introduced Delight-gated exploration (DE), a novel algorithm designed to optimize decision-making in scenarios with vast action spaces. DE prioritizes exploratory actions based on their potential "delig…
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Researchers develop semi-Markov RL for city-scale EV ride-hailing
Researchers have developed a novel semi-Markov reinforcement learning approach for optimizing city-scale electric vehicle (EV) ride-hailing fleets. This method addresses complex decisions like dispatch, repositioning, a…