Conceptual system

A conceptual system is a system of abstract concepts, of various kinds.[upper-alpha 1] The abstract concepts can range "from numbers, to emotions, and from social roles, to mental states ..".[upper-alpha 1] These abstract concepts are themselves grounded in multiple systems.[upper-alpha 1][lower-alpha 1] In psychology, a conceptual system is an individual's mental model of the world; in cognitive science the model is gradually diffused to the scientific community; in a society the model can become an institution.[lower-alpha 2] In humans, a conceptual system may be understood as kind of a metaphor for the world.[3] A belief system is composed of beliefs; Jonathan Glover, following Meadows (2008)[lower-alpha 1] suggests that tenets of belief, once held by tenants, are surprisingly difficult for the tenants to reverse, or to unhold, tenet by tenet.[14][15][9][10]

Example of a conceptual system: Earth and its Moon (as seen from Mars).[lower-alpha 3]

Thomas Nagel (1974) identified a thought experiment for non-humans in "What is it like to be a bat?".[16] David Premack and Ann James Premack (1983) assert that some non-humans (such as apes) can understand a non-human language.[17]

The earliest activities in the description of language have been attributed to the 6th-century-BC Indian grammarian Pāṇini[18][19] who wrote a formal description of the Sanskrit language in his Aṣṭādhyāyī (Devanagari अष्टाध्यायी).[20][21] Today, modern-day theories on grammar employ many of the principles that were laid down then.[22]

In the formal sciences, formal systems can have an ontological status independent of human thought, which cross across languages. Formal logical systems in a fixed formal language are an object of study. Logical forms can be objects in these formal systems. Abstract rewriting systems can operate on these objects. Axiomatic systems, and logic systems build upon axioms, and upon logical rules respectively, for their rewriting actions. Proof assistants are finding acceptance in the mathematical community.[lower-alpha 4] Artificial intelligence in machines and systems need not be restricted to hardware, but can confer a relative advantage to the institutions that adopt it, and adapt to it.[25][lower-alpha 5] Canonical forms in a suitable format and in a critical mass for acceptance can be monitored, commented upon, adopted, and applied by cooperating institutions in an upward spiral. See Best practice

In technology, Chiplets are tiny hardware subsystem implementations of SoCs (systems on a chip) which can be interconnected into larger, or more responsive surroundings. Packaging SoCs into small hardware multi-chip packages allows more effective functions which confer a competive advantage in economics, wars, or politics.[26]

See also

Notes and references
  1. The theme of the issue on Varieties of abstract concepts (18 June 2018) is "grounded in sensorimotor systems, linguistic, emotional, and social experiences".[1] Section 3a of the 5 Aug 2018 issue is "grounding of abstract concepts in multiple systems" (such as sociality, linguistics, perception action, interoception, and metacognition See figure 1).[1]
  1. Anna M Borghi, Laura Barca, Ferdinand Binkofski, and Luca Tommolini (18 June 2018) "Varieties of abstract concepts: development, use, and representation in the brain" Philosophical Transactions of the Royal Society B Biological sciences, vol 373 issue 1752 (5 Aug 2018)
  2. Hodgson (2015 p. 501), Journal of Institutional Economics (2015), 11: 3, 497–505.
  3. Lakoff, George (1980). "The Metaphorical Structure of the Human Conceptual System". Cognitive Science. 4 (2): 195–208. doi:10.1207/s15516709cog0402_4. S2CID 8800759.
  4. Dana Meadows (1993) Thinking In Systems: A Primer
  5. Donella H. Meadows (1977) A Philosophical Look at System Dynamics 53:18
  6. Ashley Hodgson Thinking in Systems, Key Ideas (Ch. 1)
  7. Ashley Hodgson Thinking in Systems, Ch. 2: Types of System Dynamics 2a
  8. Ashley Hodgson Thinking in Systems, Ch. 2, Part 2: Limiting Factors in Systems 2b
  9. Ashley Hodgson Thinking in Systems, Ch. 3: Resilience, Self-Organization and Hierarchy 3
  10. Ashley Hodgson Thinking in Systems, Ch. 4: Why Systems Surprise Us 4
  11. Ashley Hodgson Thinking in Systems, Ch. 5: System Traps 5
  12. Ashley Hodgson Thinking in Systems, Ch. 6: Leverage Points in Systems 6
  13. Ashley Hodgson Thinking in Systems, Ch. 7: Living with Systems 7
  14. ""Jonathan Glover on systems of belief", Philosophy Bites Podcast, Oct 9 2011". Archived from the original on 14 October 2011. Retrieved 5 July 2014.
  15. Elizabeth A. Minton, Lynn R. Khale (2014). Belief Systems, Religion, and Behavioral Economics. New York: Business Expert Press LLC. ISBN 978-1606497043. Archived from the original on 22 December 2019. Retrieved 30 April 2019.
  16. Thomas Nagel, "What is it like to be a bat?". Philosophical Review. LXXXIII (4): 435–450. Oct 1974. doi:10.2307/2183914. JSTOR 2183914.
  17. Premack, David & Premack, Ann James. (1983) The Mind of an Ape, p. 13. ISBN 0-393-01581-5.
  18. Rens Bod (2014). A New History of the Humanities: The Search for Principles and Patterns from Antiquity to the Present. Oxford University Press. ISBN 978-0-19-966521-1.
  19. "Chapter VI: Sanskrit Literature". The Imperial Gazetteer of India. Vol. 2. 1908. p. 263.
  20. "Aṣṭādhyāyī 2.0". panini.phil.hhu.de. Archived from the original on 15 April 2021. Retrieved 2021-02-27.
  21. S.C. Vasu (Tr.) (1996). The Ashtadhyayi of Panini (2 Vols.). Vedic Books. ISBN 978-81-208-0409-8. Archived from the original on 27 March 2014. Retrieved 17 September 2012.
  22. Penn, Gerald; Kiparski, Paul. "On Panini and the Generative Capacity of Contextualised Replacement Systems" (PDF). Proceedings of COLING 2012: 943–950. Archived from the original (PDF) on 15 April 2021.
  23. Siobhan Roberts The New York Times (2 Jul 2023) AI is coming for Mathematics, Too
  24. Siobhan Roberts The New York Times (4 July 2023) "A Complex Equation": Artificial Intelligence Complicates the Equation pp.D1,D4
  25. Clark, Jack (2015b). "Why 2015 Was a Breakthrough Year in Artificial Intelligence". Bloomberg.com. Archived from the original on 23 November 2016. Retrieved 23 November 2016.
  26. Breaking Defense (27 July 2023) How new modular chiplets in advanced semiconductors defend against dynamic threats
  1. Donella H. Meadows (2008), Thinking In Systems: A Primer, also extant as unpublished notes: Dana Meadows (1993), Thinking In Systems: A Primer[4][5] Overview, in video clips: Chapter 1[6] Chapter 2, part 1[7] Chapter 2, part 2[8] Chapter 3[9] Chapter 4[10] Chapter 5[11] Chapter 6[12] Chapter 7[13]
  2. Geoffrey Hodgson calls institutions "integrated systems of rules that structure social interactions".[2]
  3. Earth and Moon form a binary system whose barycenter lies within Earth itself. The effect on Earth's trajectory is observed as a "wobble" of an otherwise elliptical orbit of Earth around the Sun.
  4. Large language models (LLMs) are allowing mathematicians to revisit mathematical proofs which they have already written. These LLMs are mechanical 'proof whiners'; the LLMs provide line-by-line feedback to the mathematicians, which highlight the parts of the proof which the mathematicians need to rewrite so that the proof assistants can get past roadblocks.[23] This deep introspection allows the mathematicians deeper insight into their proofs.[23] [24]
  5. Meadows (2008)[9][10] noted that systems could be resilient, and surprising. They can display §emergent abilities which can confer a relative advantage, temporarily. Terence Tao noted that it helps when the robots are cute and non-threatening.[24]

Further reading
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