This document outlines the architectural design of the Human Behavior Simulation (HBS) system, focusing on its core components and supporting modules. The HBS system is designed to simulate complex human-like behavior through a multi-layered consciousness model, integrating learning, desire, and prediction systems.
The HBS is the central component responsible for simulating human-like behavior. It integrates various subsystems to model energy dynamics, memory, emotional states, and learning processes.
- Energy Dynamics: Manages energy levels, responsiveness, and resistance, adapting based on experiences.
- Memory System: Tracks recent experiences and influences decision-making and learning.
- Emotional State: Monitors emotional responses and adapts behavior accordingly.
- Learning Context: Manages skills, knowledge, and learning momentum.
- Core Drives: Models basic human motivations such as survival, social interaction, mastery, autonomy, and purpose.
- Personality Traits: Influences behavior through traits like openness, conscientiousness, and extraversion.
The Consciousness System is a multi-layered model that processes information at different levels of awareness.
- Conscious Layer: Handles rational and explicit processing of information.
- Subconscious Layer: Manages pattern recognition and emotional processing.
- Unconscious Layer: Integrates deep patterns and instinctive responses.
Each layer is interconnected, allowing for seamless information flow and integration.
The Learning System is responsible for acquiring and processing knowledge, enhancing skills, and adapting behavior.
- Learning Context: Tracks skills, experiences, and knowledge.
- Text Learning Context: Processes text-based knowledge, extracting concepts and relationships.
- Layered Learning: Integrates learning across consciousness levels, enhancing skill mastery and knowledge retention.
The Desire System models human desires and motivations, influencing decision-making and behavior.
- Desire Levels: Tracks how much the system wants different outcomes.
- Drive-Based Desires: Models desires based on core drives like survival and mastery.
- Knowledge Desires: Focuses on understanding, mastery, and curiosity.
The Future Prediction System anticipates potential outcomes based on current actions and states.
- Lookahead Steps: Simulates future states to predict outcomes.
- Time Discounting: Weighs near-term outcomes more heavily than distant ones.
- Outcome Memory: Remembers past patterns to improve prediction accuracy.
The HBS system integrates these components to simulate realistic human behavior. The Consciousness System processes stimuli and integrates responses across layers. The Learning System adapts based on experiences, while the Desire System modulates behavior according to internal drives. The Future Prediction System anticipates outcomes, guiding decision-making.
The Human Behavior Simulation system provides a comprehensive framework for modeling complex human-like behavior. By integrating consciousness, learning, desire, and prediction systems, it offers a robust platform for simulating and understanding human behavior dynamics.