TOPSIS-RAD adds DM-defined VPL to exclude non-viable options and DPL to cap performances before normalisation, anchoring PIS and NIS in aspirations rather than data extremes.
Observability a nalysis of SINS/GPS during in-motion alignment using singular value decomposition,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Reinforcement learning trains control policies to expose agent state through observable actions, demonstrated in an aircraft tracking simulation with little loss in primary task performance.
citing papers explorer
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TOPSIS-RAD: Ranking According to Desires
TOPSIS-RAD adds DM-defined VPL to exclude non-viable options and DPL to cap performances before normalisation, anchoring PIS and NIS in aspirations rather than data extremes.
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Training Observable Control Policies to Expose Agent State Through Actions
Reinforcement learning trains control policies to expose agent state through observable actions, demonstrated in an aircraft tracking simulation with little loss in primary task performance.