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Neuroevolution of an automobile crash warning system

Kenneth Stanley, Nate Kohl, Rini Sherony, Risto Miikkulainen
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
In this paper, a vehicle warning system is evolved to predict such crashes in the RARS driving simulator.  ...  Experiments were also run to compare training offline from previously collected data with training online in the simulator.  ...  CONCLUSION The NEAT neuroevolution method was used to evolve both drivers and crash predictors on the open road in the RARS driving simulator.  ... 
doi:10.1145/1068009.1068340 dblp:conf/gecco/StanleyKSM05 fatcat:6ptwwc4nwzdlrd4ua4eoawuoqq

Experiments on Neuroevolution and Online Weight Adaptation in Complex Environments [chapter]

Francisco José Gallego-Durán, Rafael Molina-Carmona, Faraón Llorens-Largo
2013 Lecture Notes in Computer Science  
This paper shows a new proposal for online weight adaptation in neuroevolved artificial neural networks, and presents the results of several experiments carried out in a race simulation environment.  ...  This methods have been tested in simple environments to isolate the effectiveness of adaptation from the Neuroevolution.  ...  The first most interesting question to continue this research would be why our approach seams to reach a top so fast.  ... 
doi:10.1007/978-3-642-40643-0_14 fatcat:ihye73j6ovgl5mdlzk6lc4lvhi

Neuroevolution in Games: State of the Art and Open Challenges [article]

Sebastian Risi, Julian Togelius
2015 arXiv   pre-print
We analyse the application of NE in games along five different axes, which are the role NE is chosen to play in a game, the different types of neural networks used, the way these networks are evolved,  ...  The article also highlights important open research challenges in the field.  ...  NEAT has been applied successfully to a variety of different game domains, from controlling a simulated car in The Open Car Racing Simulator (TORCS) [7] or a team of robots in the NERO game [89] to  ... 
arXiv:1410.7326v3 fatcat:yqynswodpnbgzdf52mlisix3hu

Neuroevolution in Games: State of the Art and Open Challenges

Sebastian Risi, Julian Togelius
2017 IEEE Transactions on Computational Intelligence and AI in Games  
We analyse the application of NE in games along five different axes, which are the role NE is chosen to play in a game, the different types of neural networks used, the way these networks are evolved,  ...  The article also highlights important open research challenges in the field.  ...  ACKNOWLEDGEMENTS We thank the numerous colleagues who have graciously read and commented on versions of this paper, including Kenneth O. Stanley, Julian Miller, Matt Taylor, Mark J.  ... 
doi:10.1109/tciaig.2015.2494596 fatcat:uenp54gg2vffdolr5awox2ayx4

Learning drivers for TORCS through imitation using supervised methods

Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
2009 2009 IEEE Symposium on Computational Intelligence and Games  
In this paper, we apply imitation learning to develop drivers for The Open Racing Car Simulator (TORCS).  ...  Our approach can be classified as a direct method in that it applies supervised learning to learn car racing behaviors from the data collected from other drivers.  ...  driving style using a simple 2D car simulator [4] , [5] and The Open Racing Car Simulator [6] .  ... 
doi:10.1109/cig.2009.5286480 dblp:conf/cig/CardamoneLL09 fatcat:jewvxvdxzrf5plvtsrrujzevjm

Evolving a real-world vehicle warning system

Nate Kohl, Kenneth Stanley, Risto Miikkulainen, Michael Samples, Rini Sherony
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
First, NEAT was evaluated in a complex, dynamic simulation with other cars, where it outperformed three hand-coded strawman warning policies and generated warning levels comparable with those of an open-road  ...  Third, the NEAT approach was evaluated in the real world using a robotic vehicle testbed.  ...  The next section describes the RARS driving simulator used in the simulation experiments and the NEAT neuroevolution method used to train warning networks.  ... 
doi:10.1145/1143997.1144273 dblp:conf/gecco/KohlSMSS06 fatcat:252reh2brjecvjnxma42lhdt4e

The 2009 Simulated Car Racing Championship

Daniele Loiacono, Pier Luca Lanzi, Julian Togelius, Enrique Onieva, David A Pelta, Martin V Butz, Thies D Lönneker, Luigi Cardamone, Diego Perez, Yago Sáez, Mike Preuss, Jan Quadflieg
2010 IEEE Transactions on Computational Intelligence and AI in Games  
In this paper, we overview the 2009 Simulated Car Racing Championship-an event comprising three competitions held in association with the 2009 IEEE Congress on Evolutionary Computation (CEC), the 2009  ...  Then, the five best teams describe the methods of computational intelligence they used to develop their drivers and the lessons they learned from the participation in the championship.  ...  Togelius, would like to thank all the competitors, without whom there would be no competition or championship at all.  ... 
doi:10.1109/tciaig.2010.2050590 fatcat:uqxuu55u6zgy7ne5cabbhrjeiy

A Survey of Autonomous Driving: Common Practices and Emerging Technologies [article]

Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda
2020 arXiv   pre-print
Furthermore, the state-of-the-art was implemented on our own platform and various algorithms were compared in a real-world driving setting.  ...  Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise.  ...  ALVINN was trained with neuroevolution and outperformed the direct supervised learning version [62] . A RNN was trained with neuroevolution in [63] using a driving simulator.  ... 
arXiv:1906.05113v2 fatcat:2hqztllrgjhndbc5aebduvukai

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

Ekim Yurtsever, Jacob Lambert, Alexander Carballo, Kazuya Takeda
2020 IEEE Access  
Furthermore, many stateof-the-art algorithms were implemented and compared on our own platform in a real-world driving setting.  ...  Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise.  ...  ALVINN was trained with neuroevolution and outperformed the direct supervised learning version [66] . A RNN was trained with neuroevolution in [67] using a driving simulator.  ... 
doi:10.1109/access.2020.2983149 fatcat:t3w7nopogvbhvbbkgpk3dknn5u

Human-assisted neuroevolution through shaping, advice and examples

Igor V. Karpov, Vinod K. Valsalam, Risto Miikkulainen
2011 Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11  
In order to answer this question, a humansubject experiment for comparing human-assisted machine learning methods was conducted.  ...  Many different methods for combining human expertise with machine learning in general, and evolutionary computation in particular, are possible.  ...  For example, imitation learning has been applied to learning driving policies for virtual race cars [2] .  ... 
doi:10.1145/2001576.2001628 dblp:conf/gecco/KarpovVM11 fatcat:c7jnzsnozncjfma47diayvscpe

Imitating human playing styles in Super Mario Bros

Juan Ortega, Noor Shaker, Julian Togelius, Georgios N. Yannakakis
2013 Entertainment Computing  
A version of the classic platform game "Super Mario Bros" is used as the testbed game in this study but the methods are applicable to other games that are based on character movement in space.  ...  We find that a method based on neuroevolution performs best both in terms of the instrumental similarity measure and in phenomenological evaluation by human spectators.  ...  Togelius et al. trained neural network controllers to replicate human driving styles through associating simulated sensor readings with steering and thrust controls in a simple 2D car racing game [9]  ... 
doi:10.1016/j.entcom.2012.10.001 fatcat:lwe7wacuxfdthdfxxaoev5fiui

How to Run a Successful Game-Based AI Competition

Julian Togelius
2016 IEEE Transactions on Computational Intelligence and AI in Games  
Game-based competitions are commonly used within the Computational Intelligence (CI) and Artificial Intelligence (AI) in games community to benchmark algorithms and to attract new researchers.  ...  There is also a discussion of how to write up game-based AI competitions and what we can ultimately learn from them.  ...  This model was used for the Simulated Car Racing Championship [11] , [12] and for the Level generation track of the Mario AI Championship [24] .  ... 
doi:10.1109/tciaig.2014.2365470 fatcat:pqn25zdnzvavbgs4lu4z4cjtqi

Constructing Game Agents Through Simulated Evolution [chapter]

Jacob Schrum, Risto Miikkulainen
2015 Encyclopedia of Computer Graphics and Games  
Definition: Construction of game agents through simulated evolution is the use of algorithms that model the biological of process of evolution to develop the behavior and/or morphology of game agents.  ...  Synonyms: Evolutionary computation, evolutionary algorithms, evolutionary machine-learning, neuroevolution, evolutionary agent design.  ...  (NERO), in which the player takes on the role of a virtual drill sergeant to train robot soldiers that learn via neuroevolution.  ... 
doi:10.1007/978-3-319-08234-9_15-1 fatcat:kq4jh5ro2vgz7iimdncf37uode

A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety [article]

A. M. Nascimento, L. F. Vismari, C. B. S. T. Molina, P.S. Cugnasca, J.B. Camargo Jr., J.R. de Almeida Jr., R. Inam, E. Fersman, M. V. Marquezini, A. Y. Hata
2019 arXiv   pre-print
In this non-convergent context, this paper presents a systematic literature review to paint a clear picture of the state of the art of the literature in AI on AV safety.  ...  However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications  ...  Preventing this is crucial in dynamic environments, where the obstacles, such as other UAVs, are moving [41] , Learning and simulation of the Human-Level decisions involved in driving a racing car [47  ... 
arXiv:1904.02697v1 fatcat:jsruqsy3kvcyvdyfhzo4ojfaqi

A Review of Platforms for the Development of Agent Systems [article]

Constantin-Valentin Pal, Florin Leon, Marcin Paprzycki, Maria Ganzha
2020 arXiv   pre-print
It aims to serve as a reference point for people interested in developing agent systems.  ...  This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used.  ...  Torcs -The Open Racing Car Simulator is a portable multi-platform car racing simulation. It is used as an ordinary car racing game, as AI racing game and as a research platform.  ... 
arXiv:2007.08961v1 fatcat:3ddtajdqv5fftldoqobr2y6y4u
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