PhD Student

Ohad's PhD Thesis is entitled "Reinforcement learning - from theory to behavior". His research interests lie in modeling behavior in general and specifically learning and decision making. For his research, Ohad collects empirical data in the lab settings and in the wild. Some concrete current research topics are:
* Medical decision making 
* Learning distributions from experience
* The importance of feedback in reinforcement learning
* Algorithmic frameworks for behavior engineering 
* Boredom, the value of novelty and variety seeking