NERO: Neuro-Evolving Robotic Operatives

01.06.2005 • Simulator, Strategi

Om spillet

N/A

Vis hele beskrivelsen

Detaljer

Genrer
Simulator • Strategi
Spiltilstande
Flerspiller
Spillerperspektiv
Tredjeperson
Platforme og udgivelsesdatoer

PC

01.06.2005
Spilmotorer
Torque Game Engine
Udvikler/Udgiver
DMC/IC2
Vis alle

Lignende spil

Vis alle

Beskrivelse

N/A

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.

Detaljer

Genrer
Simulator • Strategi
Spiltilstande
Flerspiller
Spillerperspektiv
Tredjeperson
Platforme og udgivelsesdatoer

PC

01.06.2005
Spilmotorer
Torque Game Engine
Udvikler/Udgiver
DMC/IC2