基于eBICA认知架构的具身智能数学模型

Embodied Intelligence Mathematical Model Based on eBICA Cognitive Architecture

摘要: 近年来具身智能异军突起，但在复杂社会环境中的适应性，亟需超越纯粹数据逻辑的深度情感认知能力。现有具身智能架构常面临情感认知计算与躯体感知隔离、自适应调节机制不足等问题。提出一种基于eBICA (emotional Brain Inspired Cognitive Architecture)的具身智能体数学模型，旨在通过情感计算、脑认知语义映射与伦理图式的数学化与自我调节学习的深度耦合机制，实现社会情感智能的可计算化。首先，建立eBICA六因子和认知图式的统一数学表征体系，消除感知–情感–行动的语义鸿沟；接着加入情感调节的自我学习模型，实现策略参数和情感增益的自适应调节；最后构建身体–情感双向动力学方程，建立身体信号与情感状态的实时互反馈模型，并提出评价指标。为构建具有深度社会理解与情感交互能力的具身智能体提供可参考的数学基础与算法框架。

Abstract: In recent years, embodied intelligence has emerged as a new force, but its adaptability in complex social environments urgently requires deep emotional cognitive capabilities that transcend pure data logic. Current embodied intelligence architectures often face issues such as the isolation of emotional cognitive computation from bodily perception and insufficient adaptive regulation mechanisms. A mathematical model of embodied intelligent agents based on eBICA (emotional Brain Inspired Cognitive Architecture) is proposed, aiming to achieve the computability of social-emotional intelligence through a deeply coupled mechanism of emotional computation, brain cognitive semantic mapping, ethical schemas, and self-regulatory learning. Firstly, a unified mathematical representation system of eBICA’s six factors and cognitive schemas is established to eliminate the semantic gap between perception-emotion-action. Then, a self-learning model for emotional regulation is incorporated to achieve adaptive regulation of strategy parameters and emotional gains. Finally, a bidirectional dynamic equation between body and emotion is constructed, establishing a real-time mutual feedback model between bodily signals and emotional states, and proposing evaluation metrics. This provides a referential mathematical foundation and algorithmic framework for constructing embodied intelligent agents with deep social understanding and emotional interaction capabilities.