Advanced Biologically-Inspired AI System

This project implements a cutting-edge, biologically-inspired AI system that combines advanced neural plasticity, reinforcement learning, language reasoning, and hierarchical task structures. It aims to achieve human-like performance on complex, multi-task learning benchmarks while demonstrating adaptive learning in dynamic environments.

Key Features

1. Advanced Neuroplasticity: Implements sophisticated neuroplasticity rules based on recent neuroscience findings, including:

   • Astrocyte modulation
   • Dendritic computation
   • Spike-timing-dependent plasticity (STDP)
   • Synaptic tagging and capture
   • Homeostatic plasticity

2. Reinforcement Learning: Integrates an advanced Actor-Critic reinforcement learning agent for improved decision-making.

3. Language Reasoning: Utilizes GPT-2 for complex reasoning and abstraction, enabling the system to generate explanations and incorporate language understanding into its decision-making process.

4. Hierarchical Task Structure: Implements a two-level hierarchical agent that can handle different levels of cognitive processes, from low-level actions to high-level goal setting.

5. Hybrid Learning System: Combines all the above components into a unified learning system that can adapt to various tasks and environments.

Project Structure

• src/: Contains the core implementation of all components
  • neural_plasticity.py: Advanced neuroplasticity models
  • reinforcement_learning.py: RL agent implementation
  • language_reasoning.py: GPT-2 based language reasoning module
  • hierarchical_agent.py: Hierarchical task structure implementation
  • hybrid_learning_system.py: Integration of all components
• experiments/: Contains scripts for running experiments
• requirements.txt: List of required Python packages
• README.md: Project documentation

Setup

1. Clone the repository
2. Create a virtual environment: python -m venv venv
3. Activate the virtual environment:
   • On Unix or MacOS: source venv/bin/activate
   • On Windows: venv\Scripts\activate
4. Install dependencies: pip install -r requirements.txt

Usage

Run the main experiment script:

python experiments/run_experiment.py

This will initialize the hybrid learning system and run a series of experiments to demonstrate its capabilities across various tasks and environments.