Bridging Values and Behavior: A Hierarchical Framework for Proactive Embodied Agents
📰 ArXiv cs.AI
Learn how to design proactive embodied agents using a hierarchical framework that bridges values and behavior, enabling long-term self-directed actions
Action Steps
- Design a hierarchical cognitive architecture using LLM-based cognitive modules to decouple high-level value scheduling from low-level action execution
- Implement a value scheduling system that resolves motivational conflicts and enables long-term self-directed behavior
- Integrate the ValuePlanner framework with existing embodied agent architectures to enhance their autonomy and decision-making capabilities
- Test and evaluate the performance of the ValuePlanner framework in various scenarios and environments
- Apply the ValuePlanner framework to real-world applications such as robotics, autonomous vehicles, or human-computer interaction
Who Needs to Know This
AI researchers and engineers working on embodied agents, cognitive architectures, and value alignment can benefit from this framework to create more autonomous and self-directed agents
Key Insight
💡 A hierarchical framework can enable embodied agents to make decisions based on high-level values and resolve motivational conflicts, leading to more autonomous and self-directed behavior
Share This
🤖 Introducing ValuePlanner: a hierarchical framework for proactive embodied agents that bridges values and behavior #AI #EmbodiedAgents #CognitiveArchitectures
Key Takeaways
Learn how to design proactive embodied agents using a hierarchical framework that bridges values and behavior, enabling long-term self-directed actions
Full Article
Title: Bridging Values and Behavior: A Hierarchical Framework for Proactive Embodied Agents
Abstract:
arXiv:2604.27699v1 Announce Type: new Abstract: Current embodied agents are often limited to passive instruction-following or reactive need-satisfaction, lacking a stable, high-order value framework essential for long-term, self-directed behavior and resolving motivational conflicts. We introduce \textit{ValuePlanner}, a hierarchical cognitive architecture that decouples high-level value scheduling from low-level action execution. \textit{ValuePlanner} employs an LLM-based cognitive module to ge
Abstract:
arXiv:2604.27699v1 Announce Type: new Abstract: Current embodied agents are often limited to passive instruction-following or reactive need-satisfaction, lacking a stable, high-order value framework essential for long-term, self-directed behavior and resolving motivational conflicts. We introduce \textit{ValuePlanner}, a hierarchical cognitive architecture that decouples high-level value scheduling from low-level action execution. \textit{ValuePlanner} employs an LLM-based cognitive module to ge
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