Compromise-free Pathfinding on a Navigation Mesh
Authors: Michael Cui, Daniel D. Harabor, Alban Grastien
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show how that algorithm can be modiļ¬ed to support search over arbitrary sets of convex polygons and then evaluate its performance on a range of realistic and synthetic benchmark problems. 6 Empirical Analysis We test Polyanya on a variety of realistic and synthetic grid benchmarks which are described in [Sturtevant, 2012]. |
| Researcher Affiliation | Academia | Michael L. Cui Monash University Melbourne, Australia mlcui1@student.monash.edu Daniel D. Harabor Monash University Melbourne, Australia daniel.harabor@monash.edu Alban Grastien Data61, Canberra Australian National University alban.grastien@data61.csiro.au |
| Pseudocode | No | The paper describes the algorithm components but does not provide structured pseudocode or an explicit algorithm block. |
| Open Source Code | Yes | All of our source code is publicly available4. 4https://bitbucket.org/dharabor/pathfinding |
| Open Datasets | Yes | All benchmarks are available from the HOG2 online repository 2. 2https://github.com/nathansttt/hog2 |
| Dataset Splits | No | The paper mentions using 'realistic and synthetic grid benchmarks' but does not specify any dataset splits (e.g., train/validation/test percentages or counts) or cross-validation setup. |
| Hardware Specification | Yes | All experiments are performed on a 1.7 GHz Intel Core i5 machine with 4GB of RAM and running Linux 4.8.13. |
| Software Dependencies | Yes | We implemented Polyanya in C++ and compiled our code with g++ 6.3.1 using -O3. |
| Experiment Setup | No | The paper describes the algorithm's design and empirical evaluation but does not provide specific experimental setup details such as hyperparameters, training configurations, or other system-level settings beyond the general hardware and compiler used. |