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-# WholeBrainedIntelligence_WBI
-Comprehensive AI solution emulating various cognitive processes integrating multiple specialized modules. Based on the Unified Theory of Mind (UTOM) with modules for self-awareness, heuristic pattern recognition, counterfactual simulation, value affection, empathic interaction, and learning from experience.
+![DALL·E 2024-07-01 07 02 58 - A banner image for a GitHub repository named 'WholeBrainedIntelligence (WBI)', featuring an abstract brain design with interconnected nodes  The nodes](https://github.com/QuantaScriptor/WholeBrainedIntelligence_WBI/assets/170899992/7898afcc-b9d5-4692-a69a-0d56d4218769)
+# WholeBrainedIntelligence (WBI)
+
+![Build Status](https://img.shields.io/github/actions/workflow/status/QuantaScriptor/WholeBrainedIntelligence_WBI/ci.yml)
+![License](https://img.shields.io/github/license/QuantaScriptor/WholeBrainedIntelligence_WBI)
+![Contributions](https://img.shields.io/github/contributors/QuantaScriptor/WholeBrainedIntelligence_WBI)
+
+© Reece Dixon - All rights reserved.
+
+CONFIDENTIALITY NOTICE: This information is the exclusive property of Reece Dixon and is provided under strict confidentiality. Unauthorized use, reproduction, or distribution is prohibited.
+
+## Introduction
+The WholeBrainedIntelligence (WBI) system is designed to emulate various cognitive processes by integrating multiple specialized modules. It aims to advance artificial intelligence capabilities through a comprehensive approach that mirrors human cognition. This project is based on the Unified Theory of Mind (UTOM) and incorporates modules for self-awareness, heuristic pattern recognition, counterfactual simulation, value affection, empathic interaction, and learning from experience.
+
+## Table of Contents
+- [Installation](#installation)
+- [Usage](#usage)
+- [Modules](#modules)
+- [Examples](#examples)
+- [Contributing](#contributing)
+- [License](#license)
+
+## Installation
+
+### Prerequisites
+- Python 3.8 or higher
+- Git
+- Virtual environment tool (e.g., `venv`, `virtualenv`)
+- Required libraries (listed in `requirements.txt`)
+
+### Steps
+1. Clone the repository:
+    ```bash
+    git clone https://github.com/QuantaScriptor/WholeBrainedIntelligence_WBI.git
+    cd WholeBrainedIntelligence_WBI
+    ```
+
+2. Set up the virtual environment:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
+    ```
+
+3. Install dependencies:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+4. Configure the environment:
+    Create a `.env` file in the root directory and add necessary environment variables.
+
+5. Run the initial setup script:
+    ```bash
+    python setup.py
+    ```
+
+## Usage
+Initialize the WBI system and use its modules:
+
+```python
+from wbi import WBI
+
+wbi_system = WBI()
+wbi_system.self_awareness.monitor_state()
+wbi_system.heuristic_pattern_recognition.detect_patterns(data)
+wbi_system.counterfactual_simulation.simulate_scenarios(current_state)
+wbi_system.value_affection.evaluate_values(outcomes)
+wbi_system.empathic_interaction.recognize_emotions(text)
+wbi_system.learning_from_experience.collect_experiences()
+```
+
+## Modules
+- **Self-Awareness Module**: Provides self-monitoring and reflective capabilities.
+- **Heuristic Pattern Recognition Module**: Detects patterns and anomalies in data.
+- **Counterfactual Simulation Module**: Simulates alternate scenarios for decision-making.
+- **Value Affection Module**: Evaluates and assigns value to outcomes.
+- **Empathic Interaction Module**: Facilitates empathetic responses and interactions.
+- **Learning from Experience Module**: Enhances learning from past experiences.
+
+## Examples
+Refer to the `examples` directory for comprehensive examples of using the WBI system.
+
+## Contributing
+We welcome contributions! Please read our [Contributing Guidelines](CONTRIBUTING.md) for details on how to get started.
+
+## License
+This project is licensed under the RAIL License. See the [LICENSE](LICENSE) file for details.