Journal Articles Probably bounded suboptimal heuristic search. Roni Stern, Gal Dreiman, and Richard Valenzano. Artificial Intelligence, Volume 267, 2019.
On polygon numbers of circle graphs and distance hereditary graphs. Lorna Stewart and Richard Valenzano. Discrete Applied Mathematics, Volume 248, 2018.
Learning Reward Machines for Partially Observable Reinforcement Learning. Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Margarita Castro, and Sheila A. McIlraith. NeurIPS 2019.
LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith. IJCAI 2019.
Using Reward Machines for HighLevel Task Specification and Decomposition in Reinforcement Learning. Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith. ICML 2018.
Teaching Multiple Tasks to an RL Agent using LTL. Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith. AAMAS 2018.
Using Advice in ModelBased Reinforcement Learning. Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith. CCAI 2018.
An Analysis and Enhancement of the Gap Heuristic for the Pancake Puzzle. Richard Valenzano and Danniel Sihui Yang. SoCS 2017.
Searching with a Corrupted Heuristic. Levi Lelis, Richard Valenzano, Gabriel Nazar, and Roni Stern. SOCS 2016.
On the Completeness of BestFirst Search Variants That Use Random Exploration. Richard Valenzano and Fan Xie. AAAI 2016.
Using Metric Temporal Logic to Specify Scheduling Problems. Roy Luo, Richard Valenzano, Yi Li, J. Christopher Beck, and Sheila A. McIlraith. KR 2016.
WorstCase Solution Quality Analysis When Not ReExpanding Nodes in BestFirst Search. Richard Valenzano, Nathan R. Sturtevant, and Jonathan Schaeffer. AAAI 2014.
A Comparison of KnowledgeBased GBFS Enhancements and KnowledgeFree Exploration. Richard Valenzano, Nathan R. Sturtevant, Jonathan Schaeffer, and Fan Xie. ICAPS 2014.
Using Alternative Suboptimality Bounds in Heuristic Search. Richard Valenzano, Shahab Jabbari Arfaee, Jordan Thayer, Roni Stern, and Nathan R. Sturtevant. ICAPS 2013.
Evaluating StateSpace Abstractions in ExtensiveForm Games. Michael Johanson, Neil Burch, Richard Valenzano, and Michael Bowling. AAMAS 2013.
ArvandHerd: Parallel Planning with a Portfolio. Richard Valenzano, Hootan Nakhost, Martin Müller, Jonathan Schaeffer, and Nathan R. Sturtevant. ECAI 2012.
Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal SingleAgent Search Algorithms. Richard Valenzano, Nathan R. Sturtevant, Jonathan Schaeffer, Karen Buro, and Akihiro Kishimoto. ICAPS 2010.
Technical Reports A Formal Characterization of the Local Search Topology of the Pancake Puzzle. Richard Valenzano and Danniel Sihui Yang. CoRR 2017.
ArvandHerd 2014. Richard Valenzano, Hootan Nakhost, Martin Müller, Jonathan Schaeffer, and Nathan R. Sturtevant. IPC 2014.
Adding Exploration to Greedy BestFirst Search. Richard Valenzano, Nathan R. Sturtevant, and Jonathan Schaeffer. University of Alberta Technical Report TR1306, 2013.
ArvandHerd: Parallel Planning with a Portfolio. Richard Valenzano, Hootan Nakhost, Martin Müller, Jonathan Schaeffer, and Nathan R. Sturtevant. IPC 2011.
Arvand: the Art of Random Walks. Hootan Nakhost, Martin Müller, Richard Valenzano, and Fan Xie. IPC 2011.
Theses Design Decisions on Suboptimal Heuristic SearchBased Systems. Richard Valenzano. Ph.D. Thesis. University of Alberta, 2014.
Simultaneously Searching with Multiple Algorithm Settings: An Alternative to Parameter Tuning for Suboptimal SingleAgent Search. Richard Valenzano. M.Sc. Thesis. University of Alberta, 2009.
