NERO: Neuro-Evolving Robotic Operatives

2005-06-01 • Simulator, Strategy

About the game

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Details

Genres
Simulator • Strategy
Game Modes
Multiplayer
Player Perspective
Third person
Platforms and release dates

PC

2005-06-01
Game Engines
Torque Game Engine
Developer/Publisher
DMC/IC2
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Description

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NERO is an example of a new genre of games, called Machine Learning Games. Although it resembles some RTS games, there are three important differences: (1) in NERO the agents are embedded in a 3D physics simulation, (2) the agents are trainable, and (3) the game consists of two distinct phases of play. In the first phase individual players deploy agents, i.e. simulated robots, in a "sandbox" and train them to the desired tactical doctrine. Once a collection of robots has been trained, a second phase of play (either battle or territory mode) allows players to pit their robots in a battle against robots trained by some other player, to see how effective their training was. The training phase is the most innovative aspect of game play in NERO, and is also the most interesting from the perspective of AI research.

Details

Genres
Simulator • Strategy
Game Modes
Multiplayer
Player Perspective
Third person
Platforms and release dates

PC

2005-06-01
Game Engines
Torque Game Engine
Developer/Publisher
DMC/IC2