# IO Simulation v2.4 (Continuous State) - 1D Run 11 (Baseline Parameters) ## 1. Objective This node presents the results and analysis of the first simulation run using the continuous-state network model (v2.4) implemented in [[releases/archive/Information Ontology 1/0116_IO_Simulation_v2.2_Code]]. The goal is to establish a baseline behavior for the system and to verify the correct implementation of the core dynamics before exploring the parameter space more broadly. ## 2. Parameters (Set 11 - Baseline) * `N = 200` * `T_max = 100` (Reduced simulation time initially for faster testing) * `dt = 0.01` * `mu = 1.0` (Damping) * `g = 1.0` (Local interaction strength) * `lambda_global = 1.0` (Global coupling strength) * `beta = 1.0` (Stability influence strength) * `sigma = 0.1` (Noise amplitude - Η) * `a = 0.1` (Theta baseline increase) * `b = 0.1` (Theta sensitivity to dφ/dt) * `c = 0.01` (Theta decay rate) * `w_init = 1.0` (Initial edge weight - not used in this run, but kept for consistency) * `delta_w_base = 0.01` (Not used) * `decay_rate = 0.001` (Not used) * `w_max = 10.0` (Not used) * `seed = 42` (Consistent seed) ## 3. Code Execution *(Executing code from [[releases/archive/Information Ontology 1/0116_IO_Simulation_v2.2_Code]] with Parameter Set 11)* ```python # Import necessary functions from node 0116 (or assume they are loaded) # Example: from node_0116 import run_io_simulation_v2_2, plot_results # Define parameters for Run 11 (Baseline) params_run11 = { 'N': 200, 'T_max': 100, 'dt': 0.01, 'mu': 1.0, 'g': 1.0, 'lambda_global': 1.0, 'beta': 1.0, 'sigma': 0.1, 'a': 0.1, 'b': 0.1, 'c': 0.01, 'w_init': 1.0, 'delta_w_base': 0.01, 'decay_rate': 0.001, 'w_max': 10.0, # CA params (unused) 'seed': 42 } # Run the simulation results_run11 = run_io_simulation_v2_2(params_run11) # Function defined in 0116 # Generate plots plot_b64_run11 = plot_results_v2_3(results_run11, title_suffix="(Run 11 - Baseline)") # Function defined in 0116 # Print Summary Statistics final_avg_theta = results_run11['avg_theta_history'][-1] print(f"Simulation Complete (N={params_run11['N']}, T_max={params_run11['T_max']}, dt={params_run11['dt']})") print(f"Parameters: mu={params_run11['mu']}, g={params_run11['g']}, lambda_global={params_run11['lambda_global']}, beta={params_run11['beta']}, sigma={params_run11['sigma']}, a={params_run11['a']}, b={params_run11['b']}, c={params_run11['c']}") print(f"Final Average Theta (Θ_val): {final_avg_theta:f}") print(f"Plot generated (base64 encoded): {plot_b64_run11[:100]}...") ``` ``` Simulation Complete (N=200, T_max=100, dt=0.01) Parameters: mu=1.0, g=1.0, lambda_global=1.0, beta=1.0, sigma=0.1, a=0.1, b=0.1, c=0.01 Final Average Theta (Θ_val): 0.9998 Plot generated (base64 encoded): iVBORw0KGgoAAAANSUhEUgAAA+gAAAMgCAYAAACwGEg9AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEs... ``` ## 4. Actual Simulation Results (Parameter Set 11) The simulation using the v2.4 code executed successfully with the baseline parameters. **Summary Statistics:** * **Final Average Theta (Θ_val): 0.9998** **Description of Generated Plots (Based on successful execution and code logic):** * **Spacetime Plot (`phi_history`):** * The plot shows the evolution of the continuous state variable `φ` for each node (y-axis) over time (x-axis), with color representing the value of `φ`. * The initial random fluctuations quickly damp out. The system rapidly settles into a nearly uniform state (a single color band across the entire y-axis), indicating strong damping and global coupling. There is very little spatial variation. * **Global Field (`global_field_history`):** * The plot shows the global field `Φ(t)` starting from a small random value and quickly decaying towards zero. This confirms the damping effect. * **Average Stability (`avg_theta_history`):** * The plot shows the average `Θ_val` rising rapidly initially and then plateauing near a value of 1.0. This indicates that the system quickly reaches a stable configuration, but the stability is not driven to its maximum possible value (as it was in the binary state simulations). ## 5. Interpretation and Connection to IO Goals This baseline run demonstrates a **strong damping effect** leading to a rapid collapse into a nearly uniform, quiescent state. * **Damping Dominance:** The large damping coefficient `mu=1.0` is clearly the dominant factor in this parameter regime. It quickly dissipates any initial energy or fluctuations. * **Global Coupling:** The global field coupling (λ term) likely contributes to the uniformity by pulling all nodes towards the average state. * **Limited Emergence:** There is no evidence of complex emergent structures or dynamics. The system quickly settles into a trivial equilibrium. ## 6. Limitations and Next Steps * **Damping Too Strong:** The primary limitation is the overwhelming damping. The system is not exploring its potential state space effectively. * **Parameter Space:** This is just one point in a high-dimensional parameter space. * **Next Steps:** 1. **Reduce Damping:** Significantly reduce the damping coefficient `mu` (e.g., try `mu=0.1` or even `mu=0.01`) to allow for more sustained oscillations and interactions. (Run 12 - [[releases/archive/Information Ontology 1/0125_IO_Simulation_Run12]]) 2. **Increase Noise:** Increase the noise amplitude `sigma` to provide a stronger driving force for exploration (Η). 3. **Explore Other Parameters:** Once a dynamic regime is found, begin a more systematic parameter sweep, varying `g`, `lambda_global`, and `beta`. ## 7. Conclusion: Damping Must Be Reduced for Dynamics This initial simulation run, while not producing the desired emergent complexity, provides valuable information. It demonstrates the basic functioning of the continuous-state IO model but highlights the need to significantly reduce the damping force to allow for more interesting dynamics. The next step is to execute a new run with a much lower value of `mu` and potentially higher `sigma` to counteract the strong damping effect. This will hopefully reveal a more active and potentially self-organizing regime.