Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal Single-Agent Search Algorithms. - Richard Anthony Valenzano; Nathan R. Sturtevant; Jonathan Schaeffer 001; Karen Buro; Akihiro Kishimoto (SOCS, 2010)

ArvandHerd: Parallel Planning with a Portfolio. - Richard Anthony Valenzano; Hootan Nakhost; Martin Müller 003; Jonathan Schaeffer 001; Nathan R. Sturtevant (ECAI, 2012)

Alternative Forms of Bounded Suboptimal Search. - Richard Anthony Valenzano; Shahab Jabbari Arfaee; Jordan Tyler Thayer; Roni Stern (SOCS, 2012)

Using Alternative Suboptimality Bounds in Heuristic Search. - Richard Anthony Valenzano; Shahab Jabbari Arfaee; Jordan Tyler Thayer; Roni Stern; Nathan R. Sturtevant (ICAPS, 2013)

Better Time Constrained Search via Randomization and Postprocessing. - Fan Xie 001; Richard Anthony Valenzano; Martin Müller 003 (ICAPS, 2013)

Evaluating state-space abstractions in extensive-form games. - Michael Johanson; Neil Burch; Richard Anthony Valenzano; Michael Bowling (AAMAS, 2013)

Worst-Case Solution Quality Analysis When Not Re-Expanding Nodes in Best-First Search. - Richard Anthony Valenzano; Nathan R. Sturtevant; Jonathan Schaeffer 001 (AAAI, 2014)

A Comparison of Knowledge-Based GBFS Enhancements and Knowledge-Free Exploration. - Richard Anthony Valenzano; Nathan R. Sturtevant; Jonathan Schaeffer 001; Fan Xie 001 (ICAPS, 2014)

On the Completeness of Best-First Search Variants That Use Random Exploration. - Richard Anthony Valenzano; Fan Xie 001 (AAAI, 2016)

Using Metric Temporal Logic to Specify Scheduling Problems. - Roy Luo; Richard Anthony Valenzano; Yi Li 008; J. Christopher Beck; Sheila A. McIlraith (KR, 2016)

Searching with a Corrupted Heuristic. - Levi H. S. Lelis; Richard Anthony Valenzano; Gabriel L. Nazar; Roni Stern (SOCS, 2016)

An Analysis and Enhancement of the Gap Heuristic for the Pancake Puzzle. - Richard Anthony Valenzano; Danniel Sihui Yang (SOCS, 2017)

A Formal Characterization of the Local Search Topology of the Gap Heuristic. - Richard Anthony Valenzano; Danniel Sihui Yang (CoRR, 2017)

Advice-Based Exploration in Model-Based Reinforcement Learning. - Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Anthony Valenzano; Sheila A. McIlraith (Canadian AI, 2018)

Teaching Multiple Tasks to an RL Agent using LTL. - Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Anthony Valenzano; Sheila A. McIlraith (AAMAS, 2018)

Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning. - Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Anthony Valenzano; Sheila A. McIlraith (ICML, 2018)

On polygon numbers of circle graphs and distance hereditary graphs. - Lorna Stewart; Richard Anthony Valenzano (Discret. Appl. Math., 2018)

LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. - Alberto Camacho; Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Anthony Valenzano; Sheila A. McIlraith (IJCAI, 2019)

Learning Reward Machines for Partially Observable Reinforcement Learning. - Rodrigo Toro Icarte; Ethan Waldie; Toryn Q. Klassen; Richard Anthony Valenzano; Margarita P. Castro; Sheila A. McIlraith (NeurIPS, 2019)

Probably bounded suboptimal heuristic search. - Roni Stern; Gal Dreiman; Richard Anthony Valenzano (Artif. Intell., 2019)

The act of remembering: a study in partially observable reinforcement learning. - Rodrigo Toro Icarte; Richard Anthony Valenzano; Toryn Q. Klassen; Phillip J. K. Christoffersen; Amir-massoud Farahmand; Sheila A. McIlraith (CoRR, 2020)

Type-WA*: Using Exploration in Bounded Suboptimal Planning. - Eldan Cohen; Richard Anthony Valenzano; Sheila A. McIlraith (IJCAI, 2021)

Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. - Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Anthony Valenzano; Sheila A. McIlraith (J. Artif. Intell. Res., 2022)

Opti Code Pro: A Heuristic Search-based Approach to Code Refactoring. - Sourena Khanzadeh; Samad Alias Nyein Chan; Richard Valenzano; Manar H. Alalfi (CoRR, 2023)

Learning reward machines: A study in partially observable reinforcement learning. - Rodrigo Toro Icarte; Toryn Q. Klassen; Richard Valenzano; Margarita P. Castro; Ethan Waldie; Sheila A. McIlraith (Artif. Intell., 2023)

GANsemble for Small and Imbalanced Data Sets: A Baseline for Synthetic Microplastics Data. - Daniel Platnick; Sourena Khanzadeh; Alireza Sadeghian; Richard Valenzano (Canadian AI, 2024)

The Bench Transition System and Stochastic Exploration. - Dawson Tomasz; Richard Valenzano (SOCS, 2024)

Expected Runtime Comparisons Between Breadth-First Search and Constant-Depth Restarting Random Walks. - Daniel Platnick; Richard Anthony Valenzano (CoRR, 2024)