Struct BrainConfig 

pub struct BrainConfig {

    pub neuron_count: usize,
    pub input_dim: usize,
    pub hidden_dim: usize,
    pub output_dim: usize,
    pub stdp_learning_rate: f64,
    pub neuromodulation_enabled: bool,
    pub attention_heads: usize,
    pub attention_dim: usize,
    pub top_down_strength: f64,
    pub bottom_up_strength: f64,
    pub phi_threshold: f64,
    pub broadcast_threshold: f64,
    pub precision: f64,
    pub workspace_capacity: usize,
    pub pattern_dim: usize,
    pub ca3_size: usize,
    pub consolidation_threshold: f64,
    pub max_memories: usize,
    pub replay_buffer_size: usize,
    pub sleep_cycle_length: usize,
    pub sws_ratio: f64,
    pub rem_ratio: f64,
    pub auto_sleep_enabled: bool,
    pub cycles_before_sleep: u64,
    pub meta_levels: usize,
    pub max_recursion: usize,
    pub self_update_rate: f64,
    pub mirror_depth: usize,
    pub batch_size: usize,
    pub parallel_enabled: bool,
    pub default_mode: BrainMode,
}

Configuration for the Omega Brain

Fields

neuron_count: usize

Number of neurons in the spiking network

input_dim: usize

Input dimension

hidden_dim: usize

Hidden dimension

output_dim: usize

Output dimension

stdp_learning_rate: f64

STDP learning rate

neuromodulation_enabled: bool

Enable neuromodulation

attention_heads: usize

Number of attention heads

attention_dim: usize

Attention dimension

top_down_strength: f64

Top-down attention strength

bottom_up_strength: f64

Bottom-up attention strength

phi_threshold: f64

IIT integration threshold

broadcast_threshold: f64

GWT broadcast threshold

precision: f64

Free energy precision

workspace_capacity: usize

Number of workspace slots

pattern_dim: usize

Hippocampal pattern dimension

ca3_size: usize

CA3 network size

consolidation_threshold: f64

Memory consolidation threshold

max_memories: usize

Maximum memories to retain

replay_buffer_size: usize

Replay buffer size

sleep_cycle_length: usize

Sleep cycle duration (in processing cycles)

sws_ratio: f64

SWS duration ratio (0-1)

rem_ratio: f64

REM duration ratio (0-1)

auto_sleep_enabled: bool

Enable automatic sleep

cycles_before_sleep: u64

Cycles before auto-sleep

meta_levels: usize

Number of meta-cognitive levels

max_recursion: usize

Maximum recursion depth

self_update_rate: f64

Self-model update rate

mirror_depth: usize

Mirror reflection depth

batch_size: usize

Processing batch size

parallel_enabled: bool

Enable parallel processing

default_mode: BrainMode

Default brain mode

Implementations

impl BrainConfig

pub fn minimal() -> Self

Create a minimal configuration (for testing)

pub fn high_capacity() -> Self

Create a high-capacity configuration

pub fn validate(&self) -> Result<(), String>

Validate configuration

Trait Implementations

impl Clone for BrainConfig

fn clone(&self) -> BrainConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for BrainConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for BrainConfig

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for BrainConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for BrainConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.