Samuel Tenka
Papers
1
Total Citations
2
H-Index
1
About
Samuel Tenka is a rising theorist at the intersection of cognitive science, artificial intelligence, and theoretical biology. His primary research focuses on formal models of agency, particularly through the lens of active inference—a framework that reimagines intelligent behavior not as reward maximization but as uncertainty minimization guided by a generative model of the world. In his most cited work, “Active Inference as a Model of Agency” (2024), Tenka demonstrates that any physically plausible macroscopic agent must inherently balance exploration and exploitation, offering a canonical mathematical foundation for agency that unifies disparate approaches in reinforcement learning and neuroscience. Though early in his career, his contributions are already shaping discussions on how to define and engineer goal-directed systems, with his paper garnering 2 citations and growing interest from researchers in both AI and computational psychiatry. Tenka’s work stands out for its rigorous synthesis of Bayesian mechanics, control theory, and evolutionary principles, promising a deeper understanding of what it means to act, learn, and adapt.
Research Focus
Key Achievements
Top Papers
- 1Active Inference as a Model of Agency2 citations · 2024