John Angel
Papers
1
Total Citations
5
H-Index
1
About
John Angel’s research bridges artificial intelligence and developmental psychology, with a focus on creating systems that learn and reason like humans. His most-cited work, “PERI.2 Goes to Preschool and Beyond, in Search of AGI” (2023), introduces a novel framework that models early cognitive development—such as language acquisition and social interaction—to advance artificial general intelligence. By simulating preschool-level learning, Angel demonstrates how AI can achieve flexible, context-aware reasoning without massive datasets. This paper has garnered 5 citations, reflecting its early but growing influence in the AGI community. Angel’s contributions are notable for their interdisciplinary approach, merging insights from child development with machine learning architectures. His work challenges conventional AI paradigms, offering a path toward systems that learn incrementally and adaptively, much like human children. Beyond this paper, Angel has explored embodied cognition and curriculum learning, positioning him as a forward-thinking researcher in the quest for human-like AI. His efforts underscore a commitment to building machines that not only compute but truly understand.
Research Focus
Key Achievements
Top Papers
- 1PERI.2 Goes to PreSchool and Beyond, in Search of AGI5 citations · 2023