Meta-brain Models: biologically-inspired cognitive agents
نویسندگان
چکیده
Abstract Artificial Intelligence (AI) systems based solely on neural networks or symbolic computation present a representational complexity challenge. While minimal representations can produce behavioral outputs like locomotion simple decision-making, more elaborate internal might offer richer variety of behaviors. We propose that these issues be addressed with computational approach we call meta-brain models. Meta-brain models are embodied hybrid include layered components featuring varying degrees complexity. will combinations layers composed using specialized types Rather than generic black box to unify each component, this relationship mimics the neocortical-thalamic system mammalian brain, which utilizes both feedforward and feedback connectivity facilitate functional communication. Importantly, between made anatomically explicit. This allows for structural specificity incorporated into model's function in interesting ways. several functionally integrated agents perform unique tasks, from simultaneously morphogenesis perception, undergo acquisition conceptual simultaneously. Our involves creating different complexity, meta-architecture heterogeneity biological brains, an input/output methodology flexible enough accommodate cognitive functions, social interactions, adaptive behaviors generally. conclude by proposing next steps development open-source approach.
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ژورنال
عنوان ژورنال: IOP Conference Series: Materials Science and Engineering
سال: 2022
ISSN: ['1757-8981', '1757-899X']
DOI: https://doi.org/10.1088/1757-899x/1261/1/012019