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  1. The Hierarchical Evolution in Human Vision Modeling.Dana H. Ballard & Ruohan Zhang - forthcoming - Topics in Cognitive Science.
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  • The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex.Clay B. Holroyd & Tom Verguts - 2021 - Trends in Cognitive Sciences 25 (4):316-329.
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  • Moral Gridworlds: A Theoretical Proposal for Modeling Artificial Moral Cognition.Julia Haas - 2020 - Minds and Machines 30 (2):219-246.
    I describe a suite of reinforcement learning environments in which artificial agents learn to value and respond to moral content and contexts. I illustrate the core principles of the framework by characterizing one such environment, or “gridworld,” in which an agent learns to trade-off between monetary profit and fair dealing, as applied in a standard behavioral economic paradigm. I then highlight the core technical and philosophical advantages of the learning approach for modeling moral cognition, and for addressing the so-called value (...)
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  • Memory as a Computational Resource.Ishita Dasgupta & Samuel J. Gershman - 2021 - Trends in Cognitive Sciences 25 (3):240-251.
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  • The State Space of Artificial Intelligence.Holger Lyre - 2020 - Minds and Machines 30 (3):325-347.
    The goal of the paper is to develop and propose a general model of the state space of AI. Given the breathtaking progress in AI research and technologies in recent years, such conceptual work is of substantial theoretical interest. The present AI hype is mainly driven by the triumph of deep learning neural networks. As the distinguishing feature of such networks is the ability to self-learn, self-learning is identified as one important dimension of the AI state space. Another dimension is (...)
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  • Reward Prediction Error and Declarative Memory.Kate Ergo, Esther De Loof & Tom Verguts - 2020 - Trends in Cognitive Sciences 24 (5):388-397.
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