3 papers
cs.AI2026
Efficient Constraint Generation for Stochastic Shortest Path Problems
Johannes Schmalz, Felipe Trevizan
Stochastic Shortest Path problems (SSPs) are traditionally solved by computing each state's cost-to-go by applying Bellman backups. A Bellman backup updates a state's cost-to-go by…
cs.AI2025
Solving Constrained Stochastic Shortest Path Problems with Scalarisation
Johannes Schmalz, Felipe Trevizan
Constrained Stochastic Shortest Path Problems (CSSPs) model problems with probabilistic effects, where a primary cost is minimised subject to constraints over secondary costs, e.g.…
cs.AI2024
Efficient Constraint Generation for Stochastic Shortest Path Problems
Johannes Schmalz, Felipe Trevizan
Current methods for solving Stochastic Shortest Path Problems (SSPs) find states' costs-to-go by applying Bellman backups, where state-of-the-art methods employ heuristics to selec…