In our pursuit to enhance goal-driven behavior in AI, we have investigated various models that prioritize decision-making and response generation aligned with specific objectives. These models are crucial for applications where the AI needs to perform tasks or provide information that meets predefined goals.

Key areas of our research include:

• Reinforcement Learning: Utilizing reinforcement learning techniques to train the model on goal-oriented tasks, allowing it to learn from rewards and penalties associated with achieving specific outcomes.
• Hierarchical Task Planning: Implementing hierarchical models that break down complex tasks into smaller, manageable sub-tasks, enabling the AI to achieve its goals step-by-step.
• Contextual Goal Management: Ensuring that the model can maintain and adjust its goals based on the context of the conversation, improving its ability to deliver relevant and goal-aligned responses throughout the interaction.