Perception is not a passive reconstruction of external stimuli but emerges through active, embodied interaction with the environment, according to a theoretical integration of embodied cognition and artificial intelligence. Evidence from neuroscience, developmental psychology, autism research, and AI shows that perceptual meaning arises from lawful relations among bodily constraints, action, and environmental feedback. Recent AI models like embodied reinforcement learning and active inference treat perception as inseparable from action, using closed-loop, predictive systems. The paper argues that embodiment functions as a generative constraint enabling robust sensory cognition. It extends this framework to autism spectrum disorder, proposing that sensory differences reflect variations in embodied self-organization and predictive regulation rather than cognitive deficits. Embodied AI systems could serve as testbeds for exploring these perceptual mechanisms.
Imagination is formally specified as imaginative generativity (IG), a transdisciplinary construct describing how organisms produce novel multisensory imaginings. This capacity allows anticipation of environmental changes and guides internally directed actions, supporting adaptive behavior that may influence species-level development. The paper distinguishes IG from related processes like vivid representing and mental imagery, situates this distinction within an evolutionary and archaeological account of representational change, and uses contemporary AI systems as comparative cases to identify restricted functional analogues of IG. Evidence from neuroscience, biology, and cognitive science is integrated to refine understanding of imaginative processes and their relationship to cognition and consciousness.