Multi-Agent Pathfinding as a Combinatorial Auction
Authors: Ofra Amir, Guni Sharon, Roni Stern
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conducted an empirical evaluation of the proposed approach on a range of standard MAPF benchmarks (Sturtevant 2012), comparing it with state-of-the-art optimal MAPF algorithms. |
| Researcher Affiliation | Academia | Ofra Amir School of Engineering and Applied Sciences Harvard University oamir@seas.harvard.edu Guni Sharon and Roni Stern Department of Information Systems Engineering Ben Gurion University of the Negev {gunisharon, roni.stern}@gmail.com |
| Pseudocode | No | The paper describes the stages of the i Bundle mechanism but does not present them in formal pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide a direct link to a code repository or explicitly state that source code for its methodology is made available. |
| Open Datasets | Yes | We conducted an empirical evaluation of the proposed approach on a range of standard MAPF benchmarks (Sturtevant 2012) |
| Dataset Splits | No | The paper mentions using 'standard MAPF benchmarks' but does not specify training, validation, or test dataset splits (e.g., percentages or sample counts). |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., CPU, GPU models, memory, or cloud resources) used for running the experiments. |
| Software Dependencies | No | The paper refers to existing algorithms and techniques (e.g., ICTS), but it does not list specific software dependencies with version numbers for its own implementation. |
| Experiment Setup | Yes | Price updating in i Bundle works as follows: initial prices for all bundles are 0. At the end of each round, the prices of bundles that unhappy agents bid on are raised to the maximal amount bid on the bundle by an unhappy agent plus ϵ, where ϵ is a parameter of the auction. (...) In MAPF, it is sufficient to set ϵ to the minimal edge cost to preserve optimality, because a lower increment in price will not lead to a change in agents bids. |