Bodh

बोध (Sanskrit: awareness, understanding) — Psychology engine for cognition, perception, learning, and decision-making.

Part of the AGNOS science crate ecosystem.

Key Capabilities

• Psychophysics: Weber-Fechner law, Stevens' power law, Fitts' law, Hick's law
• Cognition: Working memory (Baddeley), dual process theory (Kahneman), cognitive load
• Learning: Ebbinghaus forgetting curve, spaced repetition, Rescorla-Wagner conditioning
• Decision-making: Prospect theory (Kahneman/Tversky), expected utility, bounded rationality
• Perception: Signal detection theory (d-prime), Gestalt principles
• Psychometrics: Cronbach's alpha, split-half reliability, Big Five measurement
• Development: Piaget stages, Erikson psychosocial stages

Quick Start

use bodh::psychophysics;

// Fitts' law: index of difficulty for a UI target
let id = psychophysics::fitts_law(256.0, 4.0).unwrap();
assert!((id - 7.0).abs() < 1e-10); // 7 bits

// Ebbinghaus forgetting curve
let retention = bodh::learning::ebbinghaus_forgetting(0.0, 1.0).unwrap();
assert!((retention - 1.0).abs() < 1e-10); // perfect at t=0

// Prospect theory value function
let gain = bodh::decision::prospect_theory_value(200.0, 100.0, 0.88, 0.88, 2.25).unwrap();
let loss = bodh::decision::prospect_theory_value(0.0, 100.0, 0.88, 0.88, 2.25).unwrap();
assert!(loss.abs() > gain.abs()); // loss aversion

Feature Flags

Consumers

• bhava — psychometric validation of personality measurements
• kiran/joshua — NPC cognition, player modeling
• agnosai — decision-making models for agents

License

GPL-3.0-only