COACH(Course of Action arCHitecture) is a strategic planning tool designed to enhance the decision-making capabilities of AI systems. It integrates with AI frameworks such as MarcoPolo to help operators plan and understand complex sequences of actions for AI agents, which is vital in environments where uncertainty is high.
Key Functions of COACH
- Strategic Planning:
- COACH is primarily used to generate, evaluate, and refine plans or courses of action (COAs) for AI systems. These plans guide human-AI teams in achieving specific goals with user-directed counterfactual analysis.
- Integrated AI Training:
- COACH works alongside reinforcement learning frameworks like MarcoPolo to improve the AI’s ability to handle long-term planning tasks. It provides a structured way for AI to simulate various scenarios and select the most effective strategies.
- Handling Complexity and Uncertainty:
- One of COACH's strengths is its ability to deal with environments where outcomes are uncertain or where the AI’s actions have complex, delayed consequences. It allows AI to adjust its plans dynamically based on real-time feedback and evolving situations.
Applications
- Research and Development: COACH provides a platform for experimenting with different planning strategies, making it valuable for academic and industry research in AI and robotics.
- Autonomous Systems: Autonomous systems, such as satellites or drones, can be trained to plan and execute complex missions with minimal human intervention.
- Military and Defense: COACH can be used in scenarios like space operations or tactical planning, where AI needs to make critical decisions in real time.
Human-AI Collaboration
· COACH is designed to make the actions of AI agents interpretable by humans, meaning that it can generate plans that humans can understand, evaluate, and even modify. This fosters better collaboration between AI systems and human operators, so that these tools can be leveraged to their fullest extent.
The GitHub repository for this product can be visited here.
