Hallucinative Topological Memory for Zero-Shot Visual Planning
Authors: Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our method on a set of simulated VP problems that require non-myopic planning, and accounting for non-trivial object properties, such as geometry, in the plans. |
| Researcher Affiliation | Academia | 1Berkeley AI Research, University of California, Berkeley 2Technion. Correspondence to: Kara Liu <karamarieliu@berkeley.edu>, Thanard Kurutach <thanard.kurutach@berkeley.edu>. |
| Pseudocode | No | The paper describes the algorithm steps in paragraph form, but does not include a formal pseudocode block or algorithm listing. |
| Open Source Code | Yes | The codebase and videos can be found at https://sites.google.com/view/hallucinativetopo logicalmemory. |
| Open Datasets | No | The paper states data is collected in a "self-supervised manner" and does not provide access information (link, DOI, formal citation) for a publicly available or open dataset used for training. |
| Dataset Splits | No | The paper mentions training data and test time, but does not explicitly specify a separate validation dataset split with percentages, sample counts, or clear identification. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU/CPU models, memory specifications, or cloud computing instance types used for experiments. It mentions using a "large GPU cluster" but no specific models. |
| Software Dependencies | No | The paper mentions "Mujoco simulation (Todorov et al., 2012)" but does not provide specific version numbers for Mujoco or any other software libraries or frameworks used. |
| Experiment Setup | Yes | For the random shooting, we used 3 iterations of the cross-entropy method with 200 sample sequences. The MPC acts for 10 steps and then replans, where the planning horizon T is set to 15 as in the original implementation. [...] Table 3. Data parameters. [...] Table 4. Planning hyperparameters. |