Goal Alignment: Re-analyzing Value Alignment Problems Using Human-Aware AI
Authors: Malek Mechergui, Sarath Sreedharan
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | For evaluation, we ran our method on a set of problems selected from standard IPC benchmark problems (International Planning Competition 2011). |
| Researcher Affiliation | Academia | Malek Mechergui, Sarath Sreedharan Colorado State University {Malek.Mechergui, Sarath.Sreedharan}@colostate.edu |
| Pseudocode | Yes | Algorithm 1: An approximation-based algorithm to find a solution to a HAGL |
| Open Source Code | Yes | The code for the experiments can be found at: https://github.com/HAPILab/Goal Alignment. |
| Open Datasets | Yes | For evaluation, we ran our method on a set of problems selected from standard IPC benchmark problems (International Planning Competition 2011). International Planning Competition. 2011. IPC Competition Domains. https://goo.gl/i35bxc. |
| Dataset Splits | No | The paper discusses using "standard IPC benchmark problems" and creating "goal specification provided to the robot by randomly deleting a predicate from the goal specification" but does not provide specific dataset split information (e.g., train/validation/test percentages or counts) for reproduction. |
| Hardware Specification | Yes | All experiments were run on a linux Alma Linux 8.9 machine with 32GB ram and 16 Intel(R) Xeon(R) 2.60GHz CPUs. |
| Software Dependencies | No | The paper mentions using "Fast Downward planner" and "A-star search with LMcut heuristic" but does not provide specific version numbers for these software dependencies. |
| Experiment Setup | Yes | we set β to one for probability calculation. |