I am a postdoc at the University of Pennsylvania. I got my PhD in Engineering from the University of Cambridge and my BSc/Diploma in Computer Engineering from the University of Chile. My background is mainly in Physics, Mathematics and Computer Science.
I research the foundations of Artificial Intelligence, Machine Learning and Cybernetics. I study the links between various topics such as Bayesian probability theory, information theory, stochastic control, economics, causality, statistical mechanics, ergodic theory and complexity theory. Other areas of interest are computational neuroscience, psychology and epistemology. Also, I'm a huge fan of minimalistic algorithms.
Most of my work centers on information-theoretic and statistical mechanical approaches to adaptive control, leading to contributions in bounded rationality models and recasting adaptive control as a causal inference problem. I have also worked on causal induction, and on game- and decision-theoretic models in computational neuroscience.
To get a sense of my work, please refer to:
|Model-based learning protects against forming habits http://t.co/H4pftySlD0 |
About 3 hours, 58 mins ago by: Pedro A. Ortega (@AdaptiveAgents)
|A quantum advantage for inferring causal structure (Nature Physics!) http://t.co/rSbpYtMMch http://t.co/wYG7O3djst |
About 9 hours, 59 mins ago by: Pedro A. Ortega (@AdaptiveAgents)
|@pierrelux @BorjaBalle Salut! Yes - I'd be delighted to hear about them! Greetings |
About 2 days, 15 hours ago by: Pedro A. Ortega (@AdaptiveAgents)
|This paper is the basis of a lot that's happening today: Feature Reinforcement Learning (2009) http://t.co/0ayFUJNY9P |
About 3 days, 3 hours ago by: Pedro A. Ortega (@AdaptiveAgents)
|David Silver's "Deep Reinforcement Learning" at NIPS 2014 http://t.co/CAPJLvawk4 via @YouTube |
About 3 days, 9 hours ago by: Pedro A. Ortega (@AdaptiveAgents)
Pedro A. Ortega
Department of Engineering
University of Pennsylvania
Off. 209, Moore Building
200 S. 33rd Street
Philadelphia, PA 19104
Email: ope [AT] seas.upenn.edu
“Man is the measure of all things: of things which are, that they are, and of things which are not, that they are not” —Protagoras
“Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.” —Dijkstra (1984) On the nature of Computing Science (EWD896)