56 research outputs found

    Intelligence as inference or forcing Occam on the world

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    We propose to perform the optimization task of Universal Artificial Intelligence (UAI) through learning a reference machine on which good programs are short. Further, we also acknowledge that the choice of reference machine that the UAI objective is based on is arbitrary and, therefore, we learn a suitable machine for the environment we are in. This is based on viewing Occam’s razor as an imperative instead of as a proposition about the world. Since this principle cannot be true for all reference machines, we need to find a machine that makes the principle true. We both want good policies and the environment to have short implementations on the machine. Such a machine is learnt iteratively through a procedure that generalizes the principle underlying the Expectation-Maximization algorithm

    Computational Methods for Stability and Control (COMSAC): The Time Has Come

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    Powerful computational fluid dynamics (CFD) tools have emerged that appear to offer significant benefits as an adjunct to the experimental methods used by the stability and control community to predict aerodynamic parameters. The decreasing costs for and increasing availability of computing hours are making these applications increasingly viable as time goes on and the cost of computing continues to drop. This paper summarizes the efforts of four organizations to utilize high-end computational fluid dynamics (CFD) tools to address the challenges of the stability and control arena. General motivation and the backdrop for these efforts will be summarized as well as examples of current applications

    Gradient estimation in dendritic reinforcement learning

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    We study synaptic plasticity in a complex neuronal cell model where NMDA-spikes can arise in certain dendritic zones. In the context of reinforcement learning, two kinds of plasticity rules are derived, zone reinforcement (ZR) and cell reinforcement (CR), which both optimize the expected reward by stochastic gradient ascent. For ZR, the synaptic plasticity response to the external reward signal is modulated exclusively by quantities which are local to the NMDA-spike initiation zone in which the synapse is situated. CR, in addition, uses nonlocal feedback from the soma of the cell, provided by mechanisms such as the backpropagating action potential. Simulation results show that, compared to ZR, the use of nonlocal feedback in CR can drastically enhance learning performance. We suggest that the availability of nonlocal feedback for learning is a key advantage of complex neurons over networks of simple point neurons, which have previously been found to be largely equivalent with regard to computational capability

    Structure and Mode-of-Action of the Two-Peptide (Class-IIb) Bacteriocins

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    This review focuses on the structure and mode-of-action of the two-peptide (class-IIb) bacteriocins that consist of two different peptides whose genes are next to each other in the same operon. Optimal antibacterial activity requires the presence of both peptides in about equal amounts. The two peptides are synthesized as preforms that contain a 15–30 residue double-glycine-type N-terminal leader sequence that is cleaved off at the C-terminal side of two glycine residues by a dedicated ABC-transporter that concomitantly transfers the bacteriocin peptides across cell membranes. Two-peptide bacteriocins render the membrane of sensitive bacteria permeable to a selected group of ions, indicating that the bacteriocins form or induce the formation of pores that display specificity with respect to the transport of molecules. Based on structure–function studies, it has been proposed that the two peptides of two-peptide bacteriocins form a membrane-penetrating helix–helix structure involving helix–helix-interacting GxxxG-motifs that are present in all characterized two-peptide bacteriocins. It has also been suggested that the membrane-penetrating helix–helix structure interacts with an integrated membrane protein, thereby triggering a conformational alteration in the protein, which in turn causes membrane-leakage. This proposed mode-of-action is similar to the mode-of-action of the pediocin-like (class-IIa) bacteriocins and lactococcin A (a class-IId bacteriocin), which bind to a membrane-embedded part of the mannose phosphotransferase permease in a manner that causes membrane-leakage and cell death

    Sequence of tRNAAsn gene of Saccharomyces cerevisiae

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    Recent Enhancements to USM3D Unstructured Flow Solver for Unsteady Flows

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    The NASA USM3D unstructured flow solver is undergoing extensions to address dynamic flow problems in support of NASA and NAVAIR efforts to study the applicability of Computational Fluid Dynamics tools for the prediction of aircraft stability and control characteristics. The initial extensions reported herein include two second-order time stepping schemes, Detached-Eddy Simulation, and grid motion. This paper reports the initial code verification and validation assessment of the dynamic flow capabilities of USM3D. The cases considered are the classic inviscid shock-tube problem, low Reynolds number wake shedding from a NACA 0012 airfoil, high Reynolds number DES-based wake shedding from a 4-to-1 length-to-diameter cylinder, and forced pitch oscillation of a NACA 0012 airfoil with inviscid and turbulent flow
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