Machine psychology: bridging human learning principles and artificial general intelligence development

Alisherov, Farkhod, Ruzikulova , Nigora

Мактабгача ва мактаб таълими · 2026-yil

Annotatsiya

The pursuit of Artificial General Intelligence (AGI) represents one of the most ambitious goals in artificialintelligence research, yet current approaches often overlook the foundational principles that govern biological intelligence.This paper introduces and examines Machine Psychology as an interdisciplinary framework that systematically integratesprinciples from learning psychology-particularly operant conditioning and Relational Frame Theory-with adaptive reasoningsystems to advance AGI development. We propose a bidirectional learning model wherein psychological principlesinform AI architecture while AI systems provide novel insights into cognitive mechanisms. Through analysis of recentimplementations using the Non-Axiomatic Reasoning System (NARS), we demonstrate how core psychological constructssuch as reinforcement learning, derived relational responding, and functional equivalence can be computationally realizedto produce flexible, context-sensitive artificial cognition. This framework addresses critical limitations in contemporaryAI systems, including brittleness in novel contexts, inability to generalize across domains, and lack of metacognitivecapabilities. The paper further explores implementation challenges specific to developing economies, using Uzbekistan’saccelerated digital transformation as a case study for culturally-adapted AGI development strategies. We conclude thatMachine Psychology offers a principled pathway toward human-level artificial intelligence while simultaneously enrichingour understanding of natural cognition.

Maqola ma’lumotlari
MualliflarAlisherov, Farkhod, Ruzikulova , Nigora
JurnalМактабгача ва мактаб таълими
NashriyotТошкент давлат педагогика университети
ISSN3060-4613, 3060-4613
Nashr sanasi2026-01-11
Jild3
TilIngliz
Ilmiy sohaPsixologiya
DOI10.5281/zenodo.17804308
Indeksga qo‘shilgan2026-08-27

DOI: 10.5281/zenodo.17804308 · Maqolaning asl sahifasi

Kalit so‘zlar

Machine Psychology, Artificial General Intelligence, Operant Conditioning, Relational Frame Theory, Cognitive Architecture, NARS, Adaptive Systems

Ilmiy soha

Psixologiya

Iqtibos keltirish

APAAlisherov, Farkhod, & Ruzikulova , Nigora (2026). MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT. Мактабгача ва мактаб таълими, 3. https://doi.org/10.5281/zenodo.17804308
GOST (OAK)Alisherov, Farkhod, Ruzikulova , Nigora MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT // Мактабгача ва мактаб таълими. – 2026. – T. 3. – DOI: 10.5281/zenodo.17804308.
MLAAlisherov, Farkhod, and Ruzikulova , Nigora. “MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT.” Мактабгача ва мактаб таълими, 3, 2026. https://doi.org/10.5281/zenodo.17804308
ChicagoAlisherov, Farkhod, and Ruzikulova , Nigora. “MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT.” Мактабгача ва мактаб таълими, 3 (2026). https://doi.org/10.5281/zenodo.17804308
HarvardAlisherov, Farkhod, and Ruzikulova , Nigora (2026) ‘MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT’, Мактабгача ва мактаб таълими, 3. https://doi.org/10.5281/zenodo.17804308
BibTeX
@article{alisherovfarkhod2026,
  title = {MACHINE PSYCHOLOGY: BRIDGING HUMAN LEARNING PRINCIPLES AND ARTIFICIAL GENERAL INTELLIGENCE DEVELOPMENT},
  author = {Alisherov, Farkhod and Ruzikulova , Nigora},
  journal = {Мактабгача ва мактаб таълими},
  year = {2026},
  volume = {3},
  doi = {10.5281/zenodo.17804308},
  url = {https://doi.org/10.5281/zenodo.17804308}
}

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