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the claim
The simplicity of a hypothesis can be objectively measured
the verdict
SUPPORTED
the evidence backs this
refutedsupported
the weight of evidence
6 sources for · 0 against

The simplicity of a hypothesis can be objectively measured using established principles from information theory, such as minimum description length, Kolmogorov complexity, and algorithmic probability.

Evidence for · 6
Minimum description length model selection of multinomial processing tree models.
2010 · cited by 9
Paper 0 uses minimum description length model selection to quantitatively evaluate and compare statistical hypotheses.
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The analysis

The retrieved papers consistently support the claim that hypothesis simplicity and model complexity can be objectively quantified using tools from information theory, algorithmic information theory, and minimum description length (MDL) frameworks. Multiple studies demonstrate how compression-based metrics successfully evaluate and optimize model structures.

More for · 5
Minimax entropy: The statistical physics of optimal models.
2025 · cited by 1
Paper 1 applies the minimum description length principle to establish optimal data compression models.
Binarized neural networks converge toward algorithmic simplicity: empirical support for the learning-as-compression hypothesis.
2026 · cited by 0
Paper 2 utilizes algorithmic information theory and complexity approximations to formalize learning as compression.
SuperARC: a test for artificial superintelligence based on compressed modelling, recursive prediction and problem complexity.
2026 · cited by 0
Paper 4 applies universal principles from algorithmic information theory to formally frame model abstraction and prediction complexity.
Simplicity and Complexity in Combinatorial Optimization.
2026 · cited by 0
Paper 9 examines formal connections between Kolmogorov complexity and optimization, supporting objective measurement of simplicity.
A novel multi objective grey wolf optimization fuzzy miner for process discovery: Incorporating robustness and explainability in model evaluation.
2026 · cited by 0
Paper 10 incorporates simplicity as a quantitatively optimized metric alongside other model evaluation criteria.
The paper trail · every fact has a biography
first checked04 Aug 2026
judged → SUPPORTED · 8104 Aug 2026
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