Rick Valenzano

We cover topics such as automated planning, search methods, experimental design, etc. Could be interesting to a variety of @CompSciGradTMU students, as well as @FEAStorontometu students, especially those doing robotics, optimization, and operations research

Excited to be teaching my grad course on heuristic search at @TorontoMetSci this fall! See sites.google.com/torontomu.ca/r… for more details. Note, the course was rescheduled from the winter to the fall. @CompSciGradTMU @TMUgraduate @FEAStorontometu @researchTMU

I was evacuated from #Jasper while camping with my husband and two young kids this week. This is my #jasperwildfire story. We arrived at Wabasso campground Sunday afternoon. It was 34 degrees, and the man at the check in booth was sweating profusely in the heat. He (1/22)

@c_a_i_a_c Congratulations @SheilaMcIlraith

This year we are happy to announce two recipients of the CAIAC Lifetime Achievement Award: Dr. Sheila McIlraith (U. Toronto) and Dr. Ghorbani Ali (U. New Brunswick). These awards recognize outstanding research excellence in AI throughout their careers. caiac.ca/en/lifetime-ac…

Excited to again be teaching my grad course on Heuristic Search at @TMU_CS . If you are interested, you can find more info at bit.ly/41WV4Av @TMUgraduate @TorontoMetSci @CompSciGradTMU Could also be interesting for Operations Research students in @FEAStorontometu

I am looking for MSc and PhD students to join my team! If you are interested in heuristic search, planning, and the intersection of these topics in RL, consider applying at torontomu.ca/cs/graduate/ . More information about me at cs.torontomu.ca/~rick.valenzano

We have postdoc positions available at U of T’s theory group. I, in particular, would love to have a differential privacy postdoc. Lots of amazing people working in TCS, ML, privacy in the area! Here is the ad cs.toronto.edu/theory/positio…. Feel free to apply or share

But the "heuristic used by Dijkstra's" satisfies that condition. The bi-directional paper is here: webdocs.cs.ualberta.ca/~nathanst/pape… The 1985 paper is here: dl.acm.org/doi/10.1145/38…

And says nothing about those with an evaluation equal to the length of the optimal path. The A*-based work also typically assumes a "consistent" heuristic, which is a triangle inequality on how the heuristic function changes from vertex to vertex

There are some differences in setting. Dijkstra finds a path from an input s to ALL other vertices, whereas A* focuses on finding one path from s to a single vertex (typically). This is why the A* work focuses on "must expand" vertices.

@thesasho This was first shown by Dechter and Pearl in 1985. There is more recent work by @nathansttt et al. that I think cleans it up a bit and extends the result to bi-directional search.

@RickValenzano Do you have a reference for this?

Interesting. I am going to have to take a look. I'm curious how it extends to A*, for which we know that any "equally informed" algorithm B (ie. with the same heuristic), A* will be at least as fast as B (aside from tie-breaking). Dijkstra's after all is just A* with no heuristic

@levilelis @IJCAIconf @JAIR_Editor @RToroIcarte @SheilaMcIlraith Good day for both of us, I see. Congratulations to you too!

@RickValenzano @IJCAIconf @JAIR_Editor @RToroIcarte @SheilaMcIlraith Congratulations, Rick!

Thrilled to announce that our JAIR paper on Reward Machines (jair.org/index.php/jair…) has won the 2023 IJCAI-JAIR Best Paper Prize @IJCAIconf @JAIR_Editor Joint work with @RToroIcarte Toryn Klassen and @SheilaMcIlraith

Excited to announce our paper on Learning Reward Machines from experience for partially observable reinforcement learning has been published as a pre-proof in AIJ. Work with @RToroIcarte @mcilraith and other : doi.org/10.1016/j.arti…

We are still accepting grad applications at @TMU_CS for Canadian students. I myself have a few positions open for people interested in heuristic search, planning, and combining those topics with RL. Check out my work at rickvalenzano.com if you are interested!

Looking forward to again be teaching a grad class on Heuristic Search and AI at @TorontoMet . If you are a student interested in attending, you can find out more at bit.ly/3bZRzUj @CompSciGradTMU

The impressive deep pattern recognition abilities of #DNN's such as #LLM's are sometimes confused for reasoning abilities I can learn to guess, with high accuracy, whether a SAT instance is satisfiable or not, but this not the same as knowing how to solve SAT. Let me explain. 1/