65 results found
    1. Computational and Systems Biology
    2. Ecology

    Collaborative hunting in artificial agents with deep reinforcement learning

    Kazushi Tsutsui, Ryoya Tanaka ... Keisuke Fujii
    Collaborative hunting, characterized by the division of roles among predators, has emerged within a group of artificial agents through deep reinforcement learning.
    1. Ecology
    2. Evolutionary Biology

    Risk-sensitive learning is a winning strategy for leading an urban invasion

    Alexis J Breen, Dominik Deffner
    Animals can thrive alongside humans by being expert judges of risk.
    1. Neuroscience

    Value representations in the rodent orbitofrontal cortex drive learning, not choice

    Kevin J Miller, Matthew M Botvinick, Carlos D Brody
    Neurons in the OFC signal expected reward specifically when this information is used for learning rather than for choosing, and silencing these neurons impairs use of this information to learn.
    1. Computational and Systems Biology
    2. Physics of Living Systems

    Conformist social learning leads to self-organised prevention against adverse bias in risky decision making

    Wataru Toyokawa, Wolfgang Gaissmaier
    Mathematical modelling and large-scale online experiments revealed that learning from others can induce 'smarter' decisions even when most individuals are biased towards adverse risk aversion.
    1. Neuroscience

    RatInABox, a toolkit for modelling locomotion and neuronal activity in continuous environments

    Tom M George, Mehul Rastogi ... Caswell Barry
    A new python package standardises and simplifies how spatial behaviour and neural representations are modelled in continuous environments.
    1. Neuroscience

    Designing optimal behavioral experiments using machine learning

    Simon Valentin, Steven Kleinegesse ... Christopher G Lucas
    Recent advances in Bayesian optimal experimental design have made it possible to improve the efficiency and informativeness of experiments using machine learning, and shed new light on considerations that affect machine learning assisted experimental designs and computational models in general.
    1. Neuroscience

    Humans perseverate on punishment avoidance goals in multigoal reinforcement learning

    Paul B Sharp, Evan M Russek ... Eran Eldar
    Humans perseverate on previously instructed goals in a novel multigoal reinforcement learning task, and do this to a greater extent for punishment avoidance goals.
    1. Neuroscience

    On the normative advantages of dopamine and striatal opponency for learning and choice

    Alana Jaskir, Michael J Frank
    A computational model of the opponent neural architecture the basal ganglia, in tandem with adaptive dopamine modulation, exhibits robust advantages over traditional learning algorithms and ties together seemingly aberrant behavioral patterns resulting from dopamine and environmental manipulations across species.
    1. Neuroscience

    Control of entropy in neural models of environmental state

    Timothy H Muller, Rogier B Mars ... Jill X O'Reilly
    Evidence for neuromodulatory control of flexibility in human neural models.
    1. Neuroscience

    Rapid learning of predictive maps with STDP and theta phase precession

    Tom M George, William de Cothi ... Caswell Barry
    A close approximation to the successor representation is learnt by a simple spike-time-dependent learning rule between cells undergoing theta phase precession.

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