Algorithmic Cognition and the Computational Nature of the Mind
- Algorithmic coding theorem (not to confuse with Shannon’s coding theorem)
A theorem that formally establishes an inversely proportional relationship between Kolmogorov-Chaitin complexity and algorithmic probability.
- Algorithmic cognition
The study of animal, human, and artificial cognition based on the theory of algorithmic probability.
- Algorithmic information theory
The literature based on the concept of Kolmogorov-Chaitin complexity and related concepts such as algorithmic probability, compression, optimal inference, the Universal Distribution, and Levin’s semi-measure.
- Algorithmic probability
The probability to produce an object from a random digital computer program whose program binary digits are chosen by chance. The calculation of algorithmic probability is a lower semi-computable problem.
- Algorithmic randomness
How removed the length of the shortest generating program is from the size of the uncompressed data that such program generates.
- Block decomposition method (BDM)
- Chekaf M, Gauvrit N, Mathy F (2014) Chunking on the fly in working memory and its relationship to intelligence. In: 55th Annual meeting of the psychonomic societyGoogle Scholar
- Gauvrit N, Kinga M (2014) The equiprobability bias from a mathematical and psychological perspective. Adv Cogn Psychol 10(4):119–130Google Scholar
- Gauvrit N, Zenil H, Tegnér J (2015) The information-theoretic and algorithmic approach to human, animal and artificial cognition. arXiv preprint arXiv:1501.04242.Google Scholar
- Kahneman D, Slovic P, Tversky A (1982) Judgment under uncertainty: heuristics and biases. Cambridge University Press, New York and Cambridge.Google Scholar
- Mach E (1914) The analysis of sensations, and the relation of the physical to the psychical. Open Court Publishing Company, ChicagoGoogle Scholar
- Maguire P, Moser P, Maguire R, Griffith V 2014 Is consciousness computable? quantifying integrated information using algorithmic information theory. arXiv preprint arXiv:1405.0126Google Scholar
- Masafumi Oizumi, Larissa Albantakis, and Giulio Tononi. From the phenomenology to the mechanisms of consciousness: integrated information theory 3.0. PLoS computational biology, 10(5):e1003588, 2014.Google Scholar
- Reznikova Z, Ryabko B (2011) Numerical competence in animals, with an insight from ants. Behaviour:405–434Google Scholar
- Reznikova Z, Ryabko B (2012) Ants and bits. IEEE Inform Theor Soc News 62(5):17–20Google Scholar
- Zenil H (2013) Algorithmic complexity of animal behaviour: from communication to cognition. In: Theory and practice of natural computing second international conference proceedings, Cáceres, Spain TPNC 2013Google Scholar
- Zenil H, Hernandez-Quiroz F (2007) On the possible computational power of the human mind. In: C. Gershenson, D. Aerts, and B. Edmonds (eds) Worldviews, science and us: philosophy and complexity. World Scientific, Singapore, pp 315–334Google Scholar
- Zenil H Marshall JAR, Tegnér J (2015a) Approximations of algorithmic and structural complexity validate cognitive-behavioural experimental results. arXiv preprint arXiv:1509.06338Google Scholar
- Zenil H, Soler-Toscano F, Kiani NA, Hernández-Orozco S, Rueda-Toicen A (2016) A decomposition method for global evaluation of Shannon entropy and local estimations of algorithmic complexity. arXiv preprint arXiv:1609.00110Google Scholar