Evolving controllers for simulated car racing using differential evolution
This paper presents an initial approach for creating autonomous controllers for the car racing game using a hybrid technique. The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known c...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Penerbit UKM
2013
|
| Online Access: | https://eprints.ums.edu.my/id/eprint/19638/1/Evolving%20controllers%20for%20simulated%20car%20racing%20using%20differential%20evolution.pdf |
| _version_ | 1825713420398231552 |
|---|---|
| author | Shi, Jun Long Chin, Kim On Teo, Jason Tze Wi Tan, Tse Guan Rayner Alfred Patricia Anthony |
| author_facet | Shi, Jun Long Chin, Kim On Teo, Jason Tze Wi Tan, Tse Guan Rayner Alfred Patricia Anthony |
| author_sort | Shi, Jun Long |
| collection | UMS |
| description | This paper presents an initial approach for creating autonomous controllers for the car racing game using a hybrid technique. The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known car racing game, namely The Open Racing Car Simulator (TORCS). TORCS is used as a platform in most of the IEEE conference competitions. The main objective of this research is to test the feasibility of the DE implementation in TORCS platform. The literature showed that the application of DE in Real Time Strategy game returned promising results in evolving the required strategy gaming controllers. Interestingly, there is still no study thus far that has been conducted in applying DE into TORCS game platform. This research result shows that DE performed well in TORCS even though a very simple fitness function was used. This indicates that DE has well-tuned the neural network weights to generate optimal and sub-optimal controllers in TORCS. |
| first_indexed | 2024-03-06T02:56:18Z |
| format | Article |
| id | ums.eprints-19638 |
| institution | Universiti Malaysia Sabah |
| language | English |
| last_indexed | 2024-03-06T02:56:18Z |
| publishDate | 2013 |
| publisher | Penerbit UKM |
| record_format | dspace |
| spelling | ums.eprints-196382018-03-29T02:11:30Z https://eprints.ums.edu.my/id/eprint/19638/ Evolving controllers for simulated car racing using differential evolution Shi, Jun Long Chin, Kim On Teo, Jason Tze Wi Tan, Tse Guan Rayner Alfred Patricia Anthony This paper presents an initial approach for creating autonomous controllers for the car racing game using a hybrid technique. The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known car racing game, namely The Open Racing Car Simulator (TORCS). TORCS is used as a platform in most of the IEEE conference competitions. The main objective of this research is to test the feasibility of the DE implementation in TORCS platform. The literature showed that the application of DE in Real Time Strategy game returned promising results in evolving the required strategy gaming controllers. Interestingly, there is still no study thus far that has been conducted in applying DE into TORCS game platform. This research result shows that DE performed well in TORCS even though a very simple fitness function was used. This indicates that DE has well-tuned the neural network weights to generate optimal and sub-optimal controllers in TORCS. Penerbit UKM 2013 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/19638/1/Evolving%20controllers%20for%20simulated%20car%20racing%20using%20differential%20evolution.pdf Shi, Jun Long and Chin, Kim On and Teo, Jason Tze Wi and Tan, Tse Guan and Rayner Alfred and Patricia Anthony (2013) Evolving controllers for simulated car racing using differential evolution. Asia-Pacific Journal of Information Technology and Multimedia, 2 (1). pp. 57-68. ISSN 2289-2192 http://ejournal.ukm.my/apjitm/article/view/4291 |
| spellingShingle | Shi, Jun Long Chin, Kim On Teo, Jason Tze Wi Tan, Tse Guan Rayner Alfred Patricia Anthony Evolving controllers for simulated car racing using differential evolution |
| title | Evolving controllers for simulated car racing using differential evolution |
| title_full | Evolving controllers for simulated car racing using differential evolution |
| title_fullStr | Evolving controllers for simulated car racing using differential evolution |
| title_full_unstemmed | Evolving controllers for simulated car racing using differential evolution |
| title_short | Evolving controllers for simulated car racing using differential evolution |
| title_sort | evolving controllers for simulated car racing using differential evolution |
| url | https://eprints.ums.edu.my/id/eprint/19638/1/Evolving%20controllers%20for%20simulated%20car%20racing%20using%20differential%20evolution.pdf |
| work_keys_str_mv | AT shijunlong evolvingcontrollersforsimulatedcarracingusingdifferentialevolution AT chinkimon evolvingcontrollersforsimulatedcarracingusingdifferentialevolution AT teojasontzewi evolvingcontrollersforsimulatedcarracingusingdifferentialevolution AT tantseguan evolvingcontrollersforsimulatedcarracingusingdifferentialevolution AT rayneralfred evolvingcontrollersforsimulatedcarracingusingdifferentialevolution AT patriciaanthony evolvingcontrollersforsimulatedcarracingusingdifferentialevolution |