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Modern computer games are at the same time an attractive application domain and an interesting testbed for the evolutionary computation techniques. In this paper we apply NeuroEvolution of Augmenting Topologies (NEAT), a well known neuroevolution approach, to evolve competitive non-player characters for a racing game. In particular, we focused on The Open(More)
We address the problem of automatically designing maps for first-person shooter (FPS) games. An efficient solution to this procedural content generation (PCG) problem could allow the design of FPS games of lower development cost with near-infinite replay value and capability to adapt to the skills and preferences of individual players. We propose a(More)
We present a framework for the procedural generation of tracks for a high-end car racing game (TORCS) using interactive evolution. The framework maintains multiple populations and allow users to work both on their own population (in single-user mode) or to collaborate with other users on a shared population. Our architecture comprises a web frontend and an(More)
— 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. In the literature, this approach is known to have led to extremely poor performance with(More)
—In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with performance improvements during each generation, our approach enables a finer grained online learning with performance improvements within each lap. We tested our approach on three(More)
— Cheating reportedly affects most of the multi-player online games and might easily jeopardize the game experience by providing an unfair competitive advantage to one player over the others. Accordingly, several efforts have been made in the past years to find reliable and scalable approaches to solve this problem. Unfortunately, cheating behaviors are(More)
First, we describe the competition regulations and the software framework. 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. The organizers provide short summaries of the other competitors. Finally, we summarize the(More)
This manual describes the competition software for the Simulated Car Racing Championship, an international competition held at major conferences in the field of Evolutionary Computation and in the field of Computational Intelligence and Games. It provides an overview of the architecture, the instructions to install the software and to run the simple drivers(More)
— Finding the racing line to follow on the track is at the root of the development of any controller in racing games. In commercial games this issue is usually addressed by using human-designed racing lines provided by domain experts and represents a rather time consuming process. In this paper we introduce a novel approach to compute the racing line(More)