Algorithmic information theory
Algorithmic information theory
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Intelligence without representation
Artificial Intelligence
Spikes: exploring the neural code
Spikes: exploring the neural code
On What Makes Certain Dynamical Systems Cognitive: A Minimally Cognitive Organization Program
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Information and representation in autonomous agents
Cognitive Systems Research
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We offer a critical review of the concept of neural information, as received within mainstream neuroscience from Artificial Intelligence. This conception of information is constructed as a conditional probability of a stimulus given a certain neural activation, a correlation that cannot be accessed by the organism and fails to explain its causal organization. We reconstruct an alternative conception of neural information: a pattern of signals that is selected by the organism (as an autonomous system) to contribute to its self-maintenance in virtue of its correlation with external conditions, a correlation that might further be evaluated by the very system.