Block-Level Goal Recognition Design
Tsz-Chiu Au
Abstract
Existing works on goal recognition design (GRD) consider the underlying domain as a classical planning domain and apply modifications to the domain to minimize the worst case distinctiveness. In this paper, we propose replacing existing modifications with blocks, which group several closely related modifications together such that a block can modify a region in a search space with respect to some design constraints. Moreover, there could be blocks within blocks such that the design space becomes hierarchical for modifications at different levels of granularity. We present 1) a new version of pruned-reduce, a successful pruning rule for GRD, for block-level GRD, and 2) a new pruning rule for pruning some branches in both hierarchical and non-hierarchical design space. Our experiments show that searching in hierarchical design spaces greatly speeds up the redesign process.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 49c10192-2edf-4515-9b57-866cec35f0c2Builds on3
- Information Shaping for Enhanced Goal Recognition of Partially-Informed AgentsSarah Keren, Haifeng Xu, Kofi Kwapong, David C. Parkes et al.AAAI 2020 · 14 citations
- Stochastic Goal Recognition Design Problems with Suboptimal AgentsChristabel Wayllace, William YeohAAAI 2022 · 3 citations
- Extended Goal Recognition Design with First-Order Computation Tree LogicTsz-Chiu AuAAAI 2022 · 2 citations
Related papers
- Generalising Planning Environment RedesignAlberto Pozanco, Ramon Fraga Pereira, Daniel BorrajoAAAI 2024 · 1 citation
- Satisficing and Optimal Generalised Planning via Goal RegressionDillon Z. Chen, Till Hofmann, Toryn Q. Klassen, Sheila A. McIlraithAAAI 2026 · 1 citation
- Reducing Goal State Divergence with Environment DesignKelsey Sikes, Sarah Keren, Sarath SreedharanAAAI 2026
- Homomorphisms of Lifted Planning Tasks: The Case for Delete-Free Relaxation HeuristicsRostislav Horcík, Daniel Fiser, Álvaro TorralbaAAAI 2022 · 6 citations
- Probabilistic Hierarchical Goal Network Planning with UCTDavid H. Chan, Mark Roberts, Dana S. NauAAAI 2026
