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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Estimating the Probability of Meeting a Deadline in Hierarchical Plans
Authors: Liat Cohen, Solomon Eyal Shimony, Gera Weiss
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We examine our approximation bounds in practice, and compare the results to exact computation of the CDF and to a simple stochastic sampling scheme. Three types of task trees are used in this evaluation: task trees used as execution plans for the ROBIL team entry in the DARPA robotics challenge (DRC simulation phase, http://in.bgu.ac.il/en/Pages/news/darpa.aspx), linear plans (seq), and plans for the Logistics domain (from IPC2 http://ipc.icaps-conference.org/). ... Results for a typical indicative subset (regretfully reduced due to page limits) are shown in table 1. |
| Researcher Affiliation | Academia | Liat Cohen and Solomon Eyal Shimony and Gera Weiss Computer Science Department Ben Gurion University of The Negev Beer-Sheva, Israel 84105 EMAIL |
| Pseudocode | Yes | Algorithm 1: Sequence (X1, . . . , Xn , ε) ... Algorithm 2: Network(τ, ε) |
| Open Source Code | No | The paper does not state that the source code for their proposed methodology is publicly available or provide a link to a repository. |
| Open Datasets | Yes | Three types of task trees are used in this evaluation: task trees used as execution plans for the ROBIL team entry in the DARPA robotics challenge (DRC simulation phase, http://in.bgu.ac.il/en/Pages/news/darpa.aspx), linear plans (seq), and plans for the Logistics domain (from IPC2 http://ipc.icaps-conference.org/). |
| Dataset Splits | No | The paper discusses evaluation results but does not explicitly provide details on training, validation, or test dataset splits (e.g., percentages or sample counts) for reproducibility. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper mentions using the JSHOP2 planner but does not provide specific version numbers for any software dependencies required to reproduce the experiments. |
| Experiment Setup | Yes | The primitive task distributions were uniform distributions discretized to M values. ... We ran the exact algorithm, our approximation algorithm with ε {0.1, 0.01, 0.001}, and a simple simulation with 103 to 107 samples (number of samples is denoted by s in the table). |