Research

I am interested in formally understanding the computational foundation of human cognition at the algorithmic level of analysis. In pursuing this, I draw on topics from theoretical computer science (e.g., design and analysis of algorithms, data structures, computational complexity, distributed computing) to formally characterize cognitive processes and their computational properties (see Algorithmic Cognitive Science), with a parallel goal of developing cognitively-informed algorithms and human-like artificial intelligence.

In my PhD dissertation, I formally presented a new mode of enquiry, Rational Minimalist Program, outlining a principled, rational methodology for studying cognition at the algorithmic level of analysis. Rational Minimalist Program makes contact with a wide range of topics in theoretical computer science, allowing for bridging theoretical computer science and cognitive psychology.

Rational Minimalist Program (in a nutshell):
The mind is minimalist-optimal: In pursuing optimality, the mind strives to use the minimal amounts of resources, i.e., to take the most economical route to its goal—the thrifty mind! For more on this, see The Minimalist Mind.

Currently, I am exploring the following topics:

• • • Formal characterizations of human rationality
    • Rational process models of human reasoning and decision-making
    • Formal science of heuristics
    • Rational accounts of cognitive biases and fallacies
    • Bringing systematic order to the cognitive fallacy zoo
    • Behavioral game theory
    • Moral decision-making
    • Emotions in decision-making
    • Computational developmental psychology
    • Animal cognition
    • Deep learning
    • Reinforcement learning
    • Causal reasoning
    • Bridging computational, algorithmic, and implementational levels of analysis
    • Neural models of decision-making