I am an Applied Research Scientist at Element AI. Previously I was a postdoctoral fellow at the University of Toronto after having completed my PhD in Computing Science at the University of Alberta.  I am interested in artificial intelligence, particularly in the areas of automated planning, heuristic search, knowledge representation, reinforcement learning, and game-playing agents. See the links to the left for a list of publications.

Contact me at x@cs.toronto.edu where x=rvalenzano (ie. replace "x" with "rvalenzano" without the quotation marks). Try and grab that email address, you meddling spambots.

You can also find me on LinkedIn.

News


December 11, 2019 - Paper appearing at NeurIPS on learning and exploiting reward machines.

August 19, 2019 - Giving a talk at Amii on our project at Element AI, and work with colleagues at UofT.

August 13, 2019 - Paper appearing at IJCAI on using formal languages for RL task specification

January 12, 2019 - Teaching a course on Reinforcement Learning for the Queen's Master of Management in AI Program.

November 9, 2018 - Final version of an AIJ paper on Probably Suboptimal Search is now available.

August 28, 2018 - Presenting paper on Reward Machines at the Montreal AI Symposium.

May 11, 2018 - Paper accepted at ICML 2018 on using finite state automata to specify reward functions in RL.

February 14, 2018 - Paper accepted at Canadian AI 2018 on using temporal logic to provide advice to an RL agent.

January 24, 2018 - Paper accepted at AAMAS 2018 on using temporal logic for specifying multiple tasks for an RL agent.

January 8, 2018 - Started working as an Applied Research Scientist at Element AI.