用自我感知先验模型让智能体自发产生目标导向行为
Emergence of Goal-Directed Behaviors via Active Inference with Self-Prior
- 构建自身体感先验模型,通过匹配过去与当前感知来驱动行为
- 在模拟环境中实现无外部奖励下自主触碰刺激物的自发行为
- 适合研究发育期智能体、内在动机机制与具身认知的学者
婴儿在无外部奖励时仍会表现出目标导向行为,如伸手触碰感官刺激,这种内在动机推动了早期对身体与环境的自发探索和学习。现有计算模型多关注探索如何获取外在奖励,而本文提出一种新型密度模型——'自身体感先验'(self-prior),用于描述智能体自身的多模态感知经验。该模型嵌入基于自由能原理的主动推理框架中,仅通过最小化历史平均感知与当前观测之间的不匹配,即可生成行为参考信号。这一机制类似于通过持续环境交互形成身体图式的过程。我们在模拟环境中验证了该方法,结果显示智能体在没有外部奖励的情况下自发朝向触觉刺激移动。研究表明,仅凭内在感知一致性优化,即可诱发早期发展阶段的意图性行为。
原文摘要 · Abstract (English)
Infants often exhibit goal-directed behaviors, such as reaching for a sensory stimulus, even when no external reward criterion is provided. These intrinsically motivated behaviors facilitate spontaneous exploration and learning of the body and environment during early developmental stages. Although computational modeling can offer insight into the mechanisms underlying such behaviors, many existing studies on intrinsic motivation focus primarily on how exploration contributes to acquiring external rewards. In this paper, we propose a novel density model for an agent's own multimodal sensory experiences, called the "self-prior," and investigate whether it can autonomously induce goal-directed behavior. Integrated within an active inference framework based on the free energy principle, the self-prior generates behavioral references purely from an intrinsic process that minimizes mismatches between average past sensory experiences and current observations. This mechanism is also analogous to the acquisition and utilization of a body schema through continuous interaction with the environment. We examine this approach in a simulated environment and confirm that the agent spontaneously reaches toward a tactile stimulus. Our study implements intrinsically motivated behavior shaped by the agent's own sensory experiences, demonstrating the spontaneous emergence of intentional behavior during early development.
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