Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
SLIM: Semi-Lazy Inference Mechanism for Plan Recognition
Authors: Reuth Mirsky, Ya’akov (Kobi) Gal
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show both theoretically and empirically that although the computational cost of this process is still exponential, there is a significant improvement in run-time when compared to a state of the art of plan recognition algorithm. We evaluated the SLIM algorithm on a simulated domain, based on AND/OR trees used by Kabanza et al. [2013]. We used their same configuration which includes 100 instances with a fixed number (100) of basic actions, five identified goals, a branching factor of 3 for AND rules in the grammar and a branching factor of 2 for OR rules. |
| Researcher Affiliation | Academia | Reuth Mirsky and Ya akov (Kobi) Gal Department of Information Systems Engineering Ben-Gurion University of the Negev, Israel {EMAIL,EMAIL} |
| Pseudocode | Yes | Figure 2: SLIM s Main Functions, which contains pseudocode blocks for 'function SLIM BOTTOM-UP', 'function COMBINEDIRECTLY', and 'function COMBINEASSIBLING'. |
| Open Source Code | No | The paper does not provide any explicit statement about releasing its source code or a link to a code repository. |
| Open Datasets | Yes | We evaluated the SLIM algorithm on a simulated domain, based on AND/OR trees used by Kabanza et al. [2013]. |
| Dataset Splits | No | The paper states '100 instances' and 'Each instance contains a sequence of 9 basic actions' for the simulated domain, but does not provide specific train, validation, or test dataset splits. |
| Hardware Specification | No | The paper states 'These tests were conducted on the same commodity computer' but does not provide specific details on the hardware used, such as GPU/CPU models, processor types, or memory. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers for replication, such as programming language versions or library versions. |
| Experiment Setup | Yes | We used their same configuration which includes 100 instances with a fixed number (100) of basic actions, five identified goals, a branching factor of 3 for AND rules in the grammar and a branching factor of 2 for OR rules. |