Learning and Solving Regular Decision Processes
Authors: Eden Abadi, Ronen I. Brafman
IJCAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically evaluate this approach, demonstrating its feasibility. |
| Researcher Affiliation | Academia | Eden Abadi and Ronen I. Brafman Department of Computer Science, Ben Gurion University, Israel abadied@post.bgu.ac.il, brafman@cs.bgu.ac.il |
| Pseudocode | Yes | The high-level pseudo-code of our algorithm, S3M (Sample, Merge, Mealy Machine), is given in Algorithm 1. |
| Open Source Code | No | The paper does not provide an explicit statement or link to its source code. |
| Open Datasets | No | The paper introduces "two new RDP domains: NM-MAB and Rotating Maze" which are custom domains and does not provide concrete access information (link, DOI, formal citation) for publicly available datasets. |
| Dataset Splits | No | The paper does not provide specific dataset split information (e.g., percentages, sample counts) for training, validation, or test sets, nor does it refer to predefined splits with citations or detailed splitting methodology. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper mentions using "EDSM implementation from the Flex Fringe library" and "UCT" but does not provide specific version numbers for these software components. |
| Experiment Setup | No | The paper mentions parameters like 'c' for UCB1, 'α' and 'ϵ' for Q-learning, 'min samples', 'ϵ' for KL divergence merging, and 'λ' for the loss function, but does not provide their specific numerical values. |