Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search

Authors: Jiaoyang Li, Ariel Felner, Eli Boyarski, Hang Ma, Sven Koenig

IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Empirically, CBS with either new heuristic significantly improves the success rate over CBS with the recent heuristic and reduces the number of expanded nodes and runtime by up to a factor of 50.
Researcher Affiliation Academia 1University of Southern California 2 Ben Gurion University of the Negev
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any concrete access information (e.g., repository link, explicit statement of code release) for the source code.
Open Datasets No We generate 50 instances with random start and goal vertices for each map and each number of agents.
Dataset Splits No The paper does not provide specific dataset split information for training, validation, or testing.
Hardware Specification Yes Our code is written in C++, and our experiments are conducted on a 2.80 GHz Intel Core i7-7700 laptop with 8 GB RAM.
Software Dependencies No The paper states, "Our code is written in C++", but does not provide specific version numbers for C++ or any libraries/frameworks used.
Experiment Setup Yes We generate 50 instances with random start and goal vertices for each map and each number of agents. Our code is written in C++, and our experiments are conducted on a 2.80 GHz Intel Core i7-7700 laptop with 8 GB RAM. We use a time limit of 1 minute for each solver on each instance.