In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian
Interest in the ANN field has recently focused on dynamical neural networks for performing temporal ...
htmlabstractIntelligence is our ability to learn appropriate responses to new stimuli and situations...
Studies of learning in simple systems (invertebrates and spinal cord) have revealed that organisms c...
According to the theory of Melioration, organisms in repeated choice settings shift their choice pre...
Much of neural network research being done is performed in simulation, with simple, uniform neuron m...
This paper describes a neural network account of misbehavior with an extant neural network model of ...
A formalism is introduced to represent the connective organization of an evolving neuronal network a...
The matching law constitutes a quantitative description of choice behavior that is often observed in...
Abstract. The majority of articial neural networks are static and life-less and do not change themse...
Are learning processes selection processes? This paper takes a slightly modified version of the acco...
Animals are proposed to learn the latent rules governing their environment in order to maximize thei...
In this report we present the results of a series of simulations in which neural networks undergo ch...
© 2020 Elsevier Ltd What happens in the brain when we learn? Ever since the foundational work of Caj...
Selective information processing in neural networks is studied through computer simulations of Pavlo...
Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in...
Interest in the ANN field has recently focused on dynamical neural networks for performing temporal ...
htmlabstractIntelligence is our ability to learn appropriate responses to new stimuli and situations...
Studies of learning in simple systems (invertebrates and spinal cord) have revealed that organisms c...
According to the theory of Melioration, organisms in repeated choice settings shift their choice pre...
Much of neural network research being done is performed in simulation, with simple, uniform neuron m...
This paper describes a neural network account of misbehavior with an extant neural network model of ...
A formalism is introduced to represent the connective organization of an evolving neuronal network a...
The matching law constitutes a quantitative description of choice behavior that is often observed in...
Abstract. The majority of articial neural networks are static and life-less and do not change themse...
Are learning processes selection processes? This paper takes a slightly modified version of the acco...
Animals are proposed to learn the latent rules governing their environment in order to maximize thei...
In this report we present the results of a series of simulations in which neural networks undergo ch...
© 2020 Elsevier Ltd What happens in the brain when we learn? Ever since the foundational work of Caj...
Selective information processing in neural networks is studied through computer simulations of Pavlo...
Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in...
Interest in the ANN field has recently focused on dynamical neural networks for performing temporal ...
htmlabstractIntelligence is our ability to learn appropriate responses to new stimuli and situations...
Studies of learning in simple systems (invertebrates and spinal cord) have revealed that organisms c...