Goal Recognition Design with Non-Observable Actions
Authors: Sarah Keren, Avigdor Gal, Erez Karpas
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical evaluation has several objectives. Having shown that reduced observability may increase wcd we first examine empirically the extent of this effect. In addition, we compare the efficiency of methods proposed for the fully observable (Keren, Gal, and Karpas 2014) and partially observable settings. Finally, we evaluate the reduction process as well as the effectiveness of action reduc-tion vs. exposure. |
| Researcher Affiliation | Academia | Sarah Keren and Avigdor Gal and Erez Karpas {sarahn@tx,avigal@ie,karpase@}.technion.ac.il Technion Israel Institute of Technology |
| Pseudocode | No | The paper describes a compilation method using definitions and mathematical expressions but does not present it in a pseudocode or algorithm block format. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | We use 4 domains of plan recognition (Ramirez and Geffner 2009), namely GRID-NAVIGATION(GRID), IPC-GRID+(GRID+), BLOCK-WORDS(BLOCK), and LOGISTICS(LOG). |
| Dataset Splits | No | The paper does not specify training, validation, or test dataset splits with percentages or sample counts. |
| Hardware Specification | Yes | The experiments were run on Intel(R) Xeon(R) CPU X5690 machines, with a time limit of 30 minutes and memory limit of 2 GB. |
| Software Dependencies | No | The paper mentions 'Fast Downward planning system (Helmert 2006)' and 'LM-CUT heuristic (Helmert and Domshlak 2009)' with their publication years, but does not provide specific software version numbers for these or other ancillary software components. |
| Experiment Setup | Yes | The experiments were run on Intel(R) Xeon(R) CPU X5690 machines, with a time limit of 30 minutes and memory limit of 2 GB. We used the Fast Downward planning system (Helmert 2006) running A* with the LM-CUT heuristic (Helmert and Domshlak 2009). |