数字生命「培养皿」里，AI竟然学会了打架、结盟、抢地盘

Core Concept - The article discusses the development of a new artificial life simulation system called PD-NCA (Petri Dish Neural Cellular Automata), which allows multiple NCA agents to compete and evolve in a shared environment, focusing on self-replication as their primary goal [2][5]. Group 1: PD-NCA Overview - PD-NCA differs significantly from traditional NCA frameworks by allowing each NCA to have independent neural network parameters that are continuously optimized during the simulation [3]. - The agents in PD-NCA interact through differentiable attack and defense channels, showcasing a dynamic relationship of both competition and cooperation [5][6]. - The system enables emergent behaviors such as cyclic dynamics, territorial defense, and spontaneous cooperation among the agents [7]. Group 2: Simulation Mechanics - The simulation operates on a discrete grid, where each cell contains information about attack channels, defense channels, and hidden states [12]. - The simulation progresses through four stages: Processing, Competition, Normalization, and State Update [13]. - A static background environment is introduced to maintain a competitive atmosphere, ensuring that agents must constantly adapt to survive [16][17]. Group 3: Learning and Optimization - Each agent's optimization goal is to maximize its territory by maximizing its overall survival rate across the grid [29]. - The learning mechanism allows agents to balance between offensive expansion and defensive territory optimization, leading to complex emergent behaviors [30][31]. - The introduction of learning significantly enhances the richness and sustainability of emergent behaviors compared to a non-learning scenario [37][38]. Group 4: Experimental Findings - Experiments indicate that the number of NCA agents, grid size, and learning processes are critical factors in generating complex dynamics and diverse behaviors within PD-NCA [38]. - The study explores the impact of grid size on NCA behavior, showing variations as the grid expands from 16x16 to 196x196 [39]. - Attempts to encourage the formation of longer hypercycle structures reveal that while modifications to the loss function were made, stable long-length hypercycles were rarely observed [43].