Minimising Undesired Task Costs in Multi-Robot Task Allocation Problems with In-Schedule Dependencies
Authors: Bradford Heap, Maurice Pagnucco
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical results show this method provides a significant reduction in the total time required to complete all tasks.We evaluate each TCD value calculation method on a variety of MRTA problems with in-schedule dependencies. We compare the overall team costs for each method to the costs obtained using standard SSI auctions and regret clearing. |
| Researcher Affiliation | Academia | Bradford Heap and Maurice Pagnucco School of Computer Science and Engineering The University of New South Wales Sydney, NSW, 2052, Australia |
| Pseudocode | Yes | Figure 1: Algorithm for Sequential Single-Item Auctions. function SSI-Auction ( T,Tri, ri, R)... |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code or a link to a code repository for the methodology described. |
| Open Datasets | Yes | Our simulated test world resembles an office-like environment with 16 rooms... This environment has become the standard testbed in recent literature (Koenig et al. 2007; 2008). |
| Dataset Splits | No | The paper describes repeating experiments on randomly generated configurations and defines the problem types tested but does not specify any train/validation/test dataset splits (e.g., percentages, sample counts, or cross-validation folds). |
| Hardware Specification | No | The paper describes the simulated environment and experimental setup (e.g., grid units, number of robots/tasks) but does not provide any specific details about the hardware (e.g., CPU, GPU models, memory) used to run the simulations or experiments. |
| Software Dependencies | No | The paper does not mention any specific software dependencies or their version numbers (e.g., programming languages, libraries, frameworks, or simulation software versions) used in the experiments. |
| Experiment Setup | Yes | We repeat each experiment on 25 randomly generated configurations of opened and closed doors, with 10 robots and 60 tasks. In each configuration, each robot starts in a different random location and every robot is supplied a map of the environment at a resolution of 510x510 grid units. A grid unit covers a 5cm by 5cm area of space and gives an overall simulated space of 25.5m by 25.5m. |