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..
Learning from Trajectories via Subgoal Discovery
Authors: Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
NeurIPS 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We perform experiments on three goal-oriented tasks on Mu Jo Co [15] with sparse terminal-only reward, which state-of-the-art RL, IL or their combinations are not able to solve. |
| Researcher Affiliation | Collaboration | 1University of California-Riverside 2Mitsubishi Electric Research Laboratories (MERL) |
| Pseudocode | Yes | Algorithm 1 Learning Sub-Goal Prediction |
| Open Source Code | No | The paper does not include an unambiguous statement about releasing code or a link to a code repository for the described methodology. |
| Open Datasets | Yes | We perform experiments on three challenging environments as shown in Fig. 2. First is Ballin-Maze Game (Bi MGame) introduced in [43]... The second environment is Ant Target which involves the Ant [44]... The third environment, Ant Maze, uses the same Ant, but in a U-shaped maze used in [35]. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | Details about the network architectures we use for πθ, πφ and fψ(s) can be found in the supplementary material. |