https://arxiv.org/abs/cs/0605024 gives a formal model of intelligence (achieving high reward in an agent/environment setup, across all computable environments weighted by their Kolmogorov complexity)
https://arxiv.org/abs/1109.5951 gives a computable approximation (dubbed AIQ, Algorithmic Intelligence Quotient), and a reference implementation using Brainfuck programs (personally I would prefer Binary Combinatory Logic or Binary Lambda Calculus ;) )
To add to it: a recent attempt at designing a psychometric test encoding human cognitive priors: https://arxiv.org/abs/1911.01547 - the ARC dataset.
https://github.com/google/BIG-bench - the most recent kitchen sink of a cognitive test, which includes the previous test as a subtask.
Apparently there are large language models (Chinchilla) that perform comparably to a median human level on this second test.