Tag: artificial-intelligence
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The ‘made-up mind’.
“The ‘made-up mind’. Deriving new hypotheses on delusions from general psychological models of belief maintenance” Highlights Contemporary definitions of delusions highlight their resistance to conflicting evidence as the core feature, but there has been little progress in understanding why even explicit confrontation with contradicting evidence seldom leads to belief revision. This review aims to generate…
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Fast, slow, & metacognitive
“Fast, slow, and metacognitive thinking in AI” Inspired by the ”thinking fast and slow” cognitive theory of human decision making, we propose a multi-agent cognitive architecture (SOFAI) that is based on ”fast”/”slow” solvers and a metacognitive module. We then present experimental results on the behavior of an instance of this architecture for AI systems that…
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Towards embodied intelligence
“Intelligent soft matter: towards embodied intelligence” Intelligent soft matter lies at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field aims to create materials with life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static…
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Known and Unknown Biases
“Known and Unknown Biases: A Framework for Contextualising and Identifying Bias in Animal Behaviour Research“ (This article discusses the bias in animal behaviour research, but – as known to most readers, I hope – humanes too are members of the animal kingdom 🙂 Biases in animal behaviour research are inevitable consequences of our societal and…
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Pathfinding: a neurodynamical account of intuition
Pathfinding: a neurodynamical account of intuition We examine the neurobiology of intuition, a term often inconsistently defined in scientific literature. While researchers generally agree that intuition represents “an experienced-based process resulting in a spontaneous tendency toward a hunch or hypothesis,” we establish a firmer neurobiological foundation by framing intuition evolutionarily as a pathfinding mechanism emerging…
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Complexity data science
“Complexity data science: A spin-off from digital twins “ Digital twins offer a new and exciting framework that has recently attracted significant interest in fields such as oncology, immunology, and cardiology. The basic idea of a digital twin is to combine simulation and learning to create a virtual model of a physical object. In this paper,…
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Resilience phenotypes derived from an active inference account of allostasis
“Resilience phenotypes derived from an active inference account of allostasis“:Within a theoretical framework of enactive allostasis, we explore active inference strategies for minimizing surprise to achieve resilience in dynamic environments. While individual differences and extrinsic protective factors traditionally account for variability in resilience trajectories following stressor exposure, the enactive model emphasizes the importance of the…
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