Planning for LTLf /LDLf Goals in Non-Markovian Fully Observable Nondeterministic Domains
Authors: Ronen I. Brafman, Giuseppe De Giacomo
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide algorithms for planning in TFONDs for general LTLf/LDLf goals, and establish tight complexity bounds w.r.t. the domain representation and the goal, separately. We also show that TFONDs are able to capture all NMFONDs in which the dependency on the history is finite state . Finally, we show that TFONDs also capture Partially Observable Nondeterministic Planning Domains (PONDs), but without referring to unobservable variables. |
| Researcher Affiliation | Academia | Ronen I. Brafman1 and Giuseppe De Giacomo2 1Ben-Gurion University, Israel 2Universit a di Roma La Sapienza , Italy |
| Pseudocode | No | The paper provides high-level algorithmic steps (e.g., 'Solving FOND for LTLf/LDLf goals' and 'Solving TFOND planning for LTLf/LDLf goals') but does not present structured pseudocode blocks or algorithms with formal input/output and control flow statements. |
| Open Source Code | No | The paper does not contain any statement about making its own source code available or provide a link to a code repository for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not utilize datasets for training or evaluation, therefore no public dataset information is provided. |
| Dataset Splits | No | The paper focuses on theoretical contributions and formalisms, without conducting experiments that would require training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or the specific hardware used. |
| Software Dependencies | No | The paper references existing FOND planners and an LDLf translator tool but does not list any specific software dependencies with version numbers used for the authors' own theoretical work or any potential computational verification. |
| Experiment Setup | No | The paper is theoretical and focuses on formalisms and complexity, thus it does not include details on experimental setup, hyperparameters, or training configurations. |