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Biological Intelligence: from Behavior to Learning Theory


Zhang, Tony (Haoyu) (2022) Biological Intelligence: from Behavior to Learning Theory. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/8z4q-8g15.


Knowing how to learn, think, and act is not just a hallmark of intelligence, but a necessity of survival for many organisms. Behavior, the complete set of actions of species, allows us to glimpse into the minds of humans and animals, and by extension, intelligence itself. Biological intelligence is characterized by fast adaptation to changes and challenges, which is what allows species to survive in natural environments from starvation and predation. To study learning in a controlled setting, we can observe the behavior evoked through decision-making tasks that make it possible to quantify and analyze learning. By modeling the extracted behavioral features, we could start to understand the possible underlying mechanisms by proposing neural theory models, and look for those signals in the brain. Understanding the neural mechanisms of learning also strengthens the basis for building intelligent machines that are flexible and adaptive to the nonstationary world we live in. In this thesis, I present works in (1) automating behavioral setups and modeling suboptimal behavior in a traditional decision-making task, (2) using an ethological navigation task to characterize fast-sequence learning, and (3) how neural theory can explain some core behavioral phenomena in (2), and be used to solve a central problem in graph search.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:intelligence, learning, theory, neuroscience, behavior, ethology, decision-making, computation
Degree Grantor:California Institute of Technology
Division:Biology and Biological Engineering
Major Option:Computation and Neural Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Perona, Pietro
Thesis Committee:
  • Yue, Yisong (chair)
  • Perona, Pietro
  • Meister, Markus
  • Bouman, Katherine L.
Defense Date:23 November 2021
Record Number:CaltechTHESIS:12152021-005204320
Persistent URL:
Related URLs:
URLURL TypeDescription II, Chapter VI adapted article III, Chapter VII adapted article IV, Chapter VIII adapted article
Zhang, Tony (Haoyu)0000-0002-5198-499X
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14449
Deposited By: Haoyu Zhang
Deposited On:18 Jan 2022 17:25
Last Modified:08 Nov 2023 00:44

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