Equi-Reward Utility Maximizing Design in Stochastic Environments
Authors: Sarah Keren, Luis Pineda, Avigdor Gal, Erez Karpas, Shlomo Zilberstein
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Evaluation shows the feasibility of the approach using standard benchmarks from the probabilistic planning competition and a benchmark we created for a vacuum cleaning robot setting. |
| Researcher Affiliation | Academia | Technion Israel Institute of Technology College of Information and Computer Sciences, University of Massachusetts Amherst |
| Pseudocode | Yes | Algorithm 1 Best First Design (BFD) |
| Open Source Code | No | The paper does not provide any explicit statement about making its source code open, nor does it provide a link to a code repository for its described methodology. |
| Open Datasets | Yes | We used five PPDDL domains from the probabilistic tracks of the sixth and eighth International Planning Competition2 (IPPC06 and IPPC08)... 2http://icaps-conference.org/index.php/main/competitions |
| Dataset Splits | No | The paper does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts) for reproducibility, beyond mentioning using instances from known competitions. |
| Hardware Specification | Yes | Each problem was tested on a Intel(R) Xeon(R) CPU X5690 machine with a budget of 1, 2 and 3. |
| Software Dependencies | No | The paper mentions using tools like 'PPDDL notation', 'LAO*', and the 'FF classical planner', but it does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | Yes | Design actions were assigned a cost of 10 4, and problems were solved using LAO* [Hansen and Zilberstein, 1998] with convergence error bound of 10 6. Each run had a 30 minutes time limit. |