Paper · S7576
Entropy-Based Search Algorithm for Experimental Design
Nested Entropy Sampling searches for informative experiments in synthetic two-dimensional landscapes. Small sample counts can become trapped at local peaks, while higher counts reduce compression. The robot example is a simulation, and reported computation savings count entropy evaluations. Finite successes do not establish global convergence or physical measurement validation.
Read the paper at arxiv.orgWhat we checked
All eight supplied PDF pages and21,186 native extracted characters were read in four complete two-page returns. All layouts, three figures, full Table1 pseudocode, eight equations and sixteen references were inspected, with three enlarged crops. Root matched native page texts and actual returns. The related final-proceedings DOI is a crosslink only. Reference10 is merely an untitled work in preparation, with no body-reading credit.
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- Tests cover two-dimensional synthetic Gaussian landscapes and100 runs per sample-count setting. Local-peak failures, missing uncertainty and lower compression at larger counts constrain generalization. A displayed100% success plateau is not a mathematical guarantee.
- The circle example is simulated, using prior robot work. The3721/855 calculation supports the stated ratio and approximately77% fewer entropy evaluations only; it does not reproduce source counts or measure total runtime, memory or physical observations.
- Move kernels, exploration steps, tolerances, seeds, raw trials, parameter-generation distributions, higher-dimensional tests and optimizer comparisons remain unavailable. Eq5 condition/C-definition and verbal ratio-order gaps remain unrepaired.
- Final proceedings, external references and source code were not read or executed. Funding is stated; detailed roles and other conflicts are unknown. No UAP observation, government access or experimental replication appears.
Cite this record
N. K. Malakar, K. H. Knuth. Entropy-Based Search Algorithm for Experimental Design. August 29, 2010. BioParity S7576. https://bioparity.io/sources/S7576Record data (JSON)