1 citations · 1 across the 3 of their papers we have counts for
3 papers
Expected Runtime Comparisons Between Breadth-First Search and Constant-Depth Restarting Random Walks
Daniel Platnick, Richard Anthony Valenzano
When greedy search algorithms encounter a local minima or plateau, the search typically devolves into a breadth-first search (BrFS), or a local search technique is used in an attem…
Opti Code Pro: A Heuristic Search-based Approach to Code Refactoring
Sourena Khanzadeh, Samad Alias Nyein Chan, Richard Valenzano +1
This paper presents an approach that evaluates best-first search methods to code refactoring. The motivation for code refactoring could be to improve the design, structure, or impl…
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning
Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen +3
Reinforcement learning (RL) is a central problem in artificial intelligence. This problem consists of defining artificial agents that can learn optimal behaviour by interacting wit…