Performance Guarantees for Homomorphisms beyond Markov Decision Processes
Authors: Sultan Javed Majeed, Marcus Hutter7659-7666
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we use similar notation and techniques of Hutter (2016) but investigate and prove optimality bounds for non-MDP state-action homomorphisms in GRL. |
| Researcher Affiliation | Academia | 1,2Research School of Computer Science, Australian National University, Australia |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper uses conceptual examples like 'Navigational Grid-world' for illustration but does not provide access information for any publicly available or open dataset used in empirical studies. |
| Dataset Splits | No | The paper is theoretical and does not provide specific dataset split information (percentages, sample counts, or citations to predefined splits) needed to reproduce data partitioning for experiments. |
| Hardware Specification | No | The paper is theoretical and does not provide specific hardware details used for running experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers needed to replicate the experiment. |
| Experiment Setup | No | The paper does not contain specific experimental setup details, such as concrete hyperparameter values or training configurations, for a reproducible experiment. It mentions 'Value Iteration (VI) (Bellman 1957) with some fixed but irrelevant parameters on the grid world' but this is within a motivational example, not a detailed experimental setup. |