In the real world, planning and decision making often take place under strict computational and time constraints. This makes optimal behavior unattainable beyond the simplest cases. In another strand of research, I investigate the algorithmic strategies that humans employ to approximate the optimal solution in a variety of domains.
How does the brain generalize previously useful strategies to novel tasks?
What is the successor representation? What is its role in biological and artificial intelligence?
How do humans transfer knowledge across different tasks?
How does the brain represent different forms of uncertainty? How do those representations determine exploratory choices?
Why do humans represent their environments hierarchically? How are these hierarchical representations learned?