Modelling dynamic decision making with the ACT-R cognitive architecture

This paper describes a model of dynamic decision making in the Dynamic Stocks and Flows (DSF) task, developed using the ACT-R cognitive architecture. This task is a simple simulation of a water tank in which the water level must be kept constant whilst the inflow and outflow changes at varying rates. The basic functions of the model are based around three steps. Firstly, the model predicts the water level in the next cycle by adding the current water level to the predicted net inflow of water. Secondly, based on this projection, the net outflow of the water is adjusted to bring the water level back to the target. Thirdly, the predicted net inflow of water is adjusted to improve its accuracy in the future. If the prediction has overestimated net inflow then it is reduced, if it has underestimated net inflow it is increased. The model was entered into a model comparison competition-the Dynamic Stocks and Flows Challenge-to model human performance on four conditions of the DSF task and then subject the model to testing on five unseen transfer conditions. The model reproduced the main features of the development data reasonably well but did not reproduce human performance well under the transfer conditions. This suggests that the principles underlying human performance across the different conditions differ considerably despite their apparent similarity. Further lessons for the future development of our model and model comparison challenges are considered

Conformational switching within aromatic, electron donor and acceptor supramolecular architectures

The Iverson group has utilized favorable interactions between aromatic units in the development of highly ordered amphiphilic foldamers, two-component liquid crystal assemblies and pseudo-DNA assemblies. The above materials are made by taking advantage of the complementary electrostatic interactions between derivatives of electron-rich 1,5-dialkoxynaphthalene (DAN) and derivatives of electron-deficient 1,4,5,8-naphthalenetetracarboxylic diimide (NDI). This dissertation describes the theme of dynamic conformational switching within the context of aromatic stacking interactions. Specifically, this work focuses on switching between an aromatic electron-rich and aromatic electron-deficient alternating stacking geometry and an aromatic electron-rich self stacking geometry. While much of this work can be partially explained using classical notions of aromatic stacking (Hunter and Sanders), a new theory explaining aromatic stacking interactions (Wheeler and Houk) is highlighted which better explains the conformational switching behavior. Chapter 2 elucidates the aggregated structure of two amphiphilic foldamers that irreversibly undergo thermally induced conformational changes to form self-supporting hydrogels. The thermodynamics and morphologies of the foldamer aggregates are similar to amyloid aggregates, the misfolded state of proteins associated in numerous neurodegenerative diseases. Chapter 3 discusses the synthesis and time dependent polymorphism of four conjugated aromatic monoalkoxynaphthalene-naphthalimide (MAN-NI) dyads. Interestingly, two dyads displayed a NI-NI stacking geometry upon slower evaporation from solution and a NI-MAN stacking geometry upon faster evaporation from solution. Chapter 4 further investigates the properties of MAN-NI dyads and demonstrates one of dyads displays solvatochromic, thermochromic, vapochromic and mechanochromic stimuli responsive behaviors. Using applied external stimuli the dyad is thought to undergo a conformational change from an NI-NI stacking geometry to a NI-MAN stacking geometry. Chapter 5 details initial investigations into MAN-NI polymers for liquid crystal polymers and organic electronic materials. Four polymers were synthesized and characterized and found to display liquid crystal mesophase textures at room temperature. Additionally, the electronic behavior of the polymers suggests they may be useful candidates for optoelectronic applications. Overall, this work sheds considerable light on the ability of aromatic materials to under conformational changes in solution and in the solid state as a consequence of favorable direct, electrostatic interactions between the aromatic units.Chemistr

Multiple representations in cognitive architectures

The widely demonstrated ability of humans to deal with multiple representations of information has a number of important implications for a proposed standard model of the mind (SMM). In this paper we outline four and argue that a SMM must incorporate (a) multiple representational formats and (b) meta-cognitive processes that operate on them. We then describe current approaches to extend cognitive architectures with visual-spatial representations, in part to illustrate the limitations of current architectures in relation to the implications we raise but also to identify the basis upon which a consensus about the nature of these additional representations can be agreed. We believe that addressing these implications and outlining a specification for multiple represen- tations should be a key goal for those seeking to develop a standard model of the mind

Sampling Random Spanning Trees Faster than Matrix Multiplication

We present an algorithm that, with high probability, generates a random spanning tree from an edge-weighted undirected graph in $\tilde{O}(n^{4/3}m^{1/2}+n^{2})$ time (The $\tilde{O}(\cdot)$ notation hides $\operatorname{polylog}(n)$ factors). The tree is sampled from a distribution where the probability of each tree is proportional to the product of its edge weights. This improves upon the previous best algorithm due to Colbourn et al. that runs in matrix multiplication time, $O(n^\omega)$. For the special case of unweighted graphs, this improves upon the best previously known running time of $\tilde{O}(\min\{n^{\omega},m\sqrt{n},m^{4/3}\})$ for $m \gg n^{5/3}$ (Colbourn et al. '96, Kelner-Madry '09, Madry et al. '15). The effective resistance metric is essential to our algorithm, as in the work of Madry et al., but we eschew determinant-based and random walk-based techniques used by previous algorithms. Instead, our algorithm is based on Gaussian elimination, and the fact that effective resistance is preserved in the graph resulting from eliminating a subset of vertices (called a Schur complement). As part of our algorithm, we show how to compute $\epsilon$-approximate effective resistances for a set $S$ of vertex pairs via approximate Schur complements in $\tilde{O}(m+(n + |S|)\epsilon^{-2})$ time, without using the Johnson-Lindenstrauss lemma which requires $\tilde{O}( \min\{(m + |S|)\epsilon^{-2}, m+n\epsilon^{-4} +|S|\epsilon^{-2}\})$ time. We combine this approximation procedure with an error correction procedure for handing edges where our estimate isn't sufficiently accurate

Semantic Photo Manipulation with a Generative Image Prior

Despite the recent success of GANs in synthesizing images conditioned on inputs such as a user sketch, text, or semantic labels, manipulating the high-level attributes of an existing natural photograph with GANs is challenging for two reasons. First, it is hard for GANs to precisely reproduce an input image. Second, after manipulation, the newly synthesized pixels often do not fit the original image. In this paper, we address these issues by adapting the image prior learned by GANs to image statistics of an individual image. Our method can accurately reconstruct the input image and synthesize new content, consistent with the appearance of the input image. We demonstrate our interactive system on several semantic image editing tasks, including synthesizing new objects consistent with background, removing unwanted objects, and changing the appearance of an object. Quantitative and qualitative comparisons against several existing methods demonstrate the effectiveness of our method.Comment: SIGGRAPH 201

Imaging Polarimeter Arrays for Near-Millimeter Waves

An integrated-circuit antenna array has been developed that images both polarization and intensity. The array consists of a row of antennas that lean alternately left and right, creating two interlaced sub-arrays that respond to different polarizations. The arrays and the bismuth bolometer detectors are made by a photoresist shadowing technique that requires only one photolithographic mask. The array has measured polarization at a wavelength of 800 µm with an absolute accuracy of 0.8° and a relative precision of 7 arc min. and has demonstrated nearly diffraction-Iimited resolutiort of a 20° step in polarization