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Found 4 papers, 0 papers with code
Geometry of Policy Improvement
We investigate the geometry of optimal memoryless time independent decision making in relation to the amount of information that the acting agent has about the state of the system.
Hierarchical Models as Marginals of Hierarchical Models
We investigate the representation of hierarchical models in terms of marginals of other hierarchical models with smaller interactions.
Quantifying Morphological Computation based on an Information Decomposition of the Sensorimotor Loop
We believe that a formal approach to quantifying the embodiment's effect on the agent's behaviour is beneficial to the fields of artificial life and artificial intelligence.
Expressive Power and Approximation Errors of Restricted Boltzmann Machines
We present explicit classes of probability distributions that can be learned by Restricted Boltzmann Machines (RBMs) depending on the number of units that they contain, and which are representative for the expressive power of the model.
