Behaviora - A Conceptual Architecture for External and Internal Behavior of Robots and Agents
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Abstract (arXiv)
Behaviora is a preliminary conceptual architecture for representing agent and robot behavior, external and internal alike, in an addressable form. A behaving robot or agent performs a Behavior Episode composed of episode components, which can be derived from behavior taxonomies (BTax) and assigned persistent identifiers. We denote these identifiers as IoB (Internet of Behaviors) Addresses. A Behavior Episode specifies what the system does, while a Style Profile (SP) specifies how this behavior is expressed. Style can communicate characteristics of the actor and qualities such as competence and cultural manners. An Experience Profile (EP) represents behaviorally relevant internal state that modulates the execution of an Episode. Finally, a Behavior Compiler maps these behavioral representations to platform-specific actions. We use a primitive touching arm model to show these components and their relations. External Behavior is a result of addressable movements and their styles. Internal Behavior is represented through the same episodic principle and can be rendered as inner speech. Sensing, perception and complex task contexts have not been included in the present implementation, although a conceptual place is reserved for them.
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References · 6
- 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 3,080
- 2017Behavior Trees in Robotics and AI: An Introductioncited by 107
- 2020Explainable Goal-Driven Agents and Robots -- A Comprehensive Reviewcited by 24
- 2022Structured Like a Language Model: Analysing AI as an Automated Subjectcited by 6
- 2024Preliminaries to artificial consciousness: a multidimensional heuristic approachcited by 4
- 2026Data Standards for Humanoid Robotics: The Missing Infrastructure for Physical AIcited by 1
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