Efficient Object Search in Game Maps
Authors: Jinchun Du, Bojie Shen, Shizhe Zhao, Muhammad Aamir Cheema, Adel Nadjaran Toosi
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our extensive experimental study, conducted on standard game maps benchmarks and real-world keywords, demonstrates that our approach has up to 2 orders of magnitude faster update times for moving objects compared to stateof-the-art approaches such as navigation mesh and IR-tree. |
| Researcher Affiliation | Academia | Jinchun Du , Bojie Shen , Shizhe Zhao , Muhammad Aamir Cheema , Adel Nadjaran Toosi Faculty of Information Technology, Monash University, Melbourne, Australia {jinchun.du, bojie.shen, shizhe.zhao, aamir.cheema, adel.n.toosi}@monash.edu |
| Pseudocode | Yes | Algorithm 1: Boolean k NN query processing |
| Open Source Code | Yes | 1https://github.com/goldi1027/GT-EHL |
| Open Datasets | Yes | We run experiments on widely used game map benchmarks [Sturtevant, 2012] of four popular games: Dragon Age II (DA); Dragon Age Origins (DAO); Baldur s Gate II (BG) and Star Craft (SC). |
| Dataset Splits | No | The paper describes generating objects, keywords, and queries, but does not specify formal training, validation, or test dataset splits or percentages. |
| Hardware Specification | Yes | We run our experiments on a 3.2 GHz Intel Core i7 machine with 32 GB of RAM. |
| Software Dependencies | No | All the algorithms are implemented in C++ and compiled with -O3 flag. The paper mentions using 'nltk, an NLP library' but does not specify its version. It also mentions 'Chat GPT (Jan 9 version)' but this is a tool used for keyword generation, not a software dependency for the algorithm itself. |
| Experiment Setup | Yes | We vary the density from 0.1% to 10% and the default density is 1%. We define mobility of an object set as the percentage of objects that move between two timestamps. We vary the mobility from 10% to 100% and the default mobility is 70%. We evaluate the effect of k which is varied from 1 to 10 where the default value of k is 3. We also evaluate the effect of number of query keywords by varying the number of query keywords from 0 to 3 where the default number of keywords is 2. For each experiment, we generate 100 queries per timestamp. |