Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.

The Role of Context-Related Parameters in Adults' Mental Computational Acts. 'El papel de los parámetros relacionados con el contexto en actos de cálculo mental en adultos'.

Resumen basado en el de la publicación

Development and cross-national validation of the Emotional Effort Scale (EEF)

Resumen tomado de la publicación

Single and multiple addition to C60. A computational chemistry study

Des del seu descobriment, a la molècula C60 se li coneixen una varietat de derivats segons el tipus de funcionalització amb propietats fisicoquímiques específiques de gran interès científic. Una sel·lecció de derivats corresponents a addicions simple o múltiple al C60 s'ha considerat en aquest treball d'investigació. L'estudi a nivell de química computacional de diversos tipus d'addició al C60 s'han portat a terme per tal de poder donar resposta a aspectes que experimentalment no s'entenen o són poc clars. Els sistemes estudiats en referència a l'addició simple al C60 han estat en primer lloc els monoiminoful·lerens, C60NR, (de les dues vies proposades per la seva síntesi, anàlisis cinètic i termodinàmic han ajudat a explicar els mecanismes de formació i justificar l'addició a enllaços tipus [5,6]), i en segon lloc els metanoful·lerens i els hidroful·lerens substituits, C60CHR i C60HR, (raons geomètriques, electròniques, energètiques i magnètiques justifiquen el diferent caràcter àcid ente ambdós derivats tenint en compte una sèrie de substituents R amb diferent caràcter electrònic donor/acceptor). Els fluoroful·lerens, C60Fn, i els epoxid ful·lerens, C60On, (anàlisi sistemàtic dels seus patrons d'addició en base a poder justificar la força que els governa han aportat dades complementàries a les poques que existeixen experimentalment al respecte).

Memory-based Embodied Cognition: a computational architecture

At its most fundamental, cognition as displayed by biological agents (such as humans) may be said to consist of the manipulation and utilisation of memory. Recent discussions in the field of cognitive robotics have emphasised the role of embodiment and the necessity of a value or motivation for autonomous behaviour. This work proposes a computational architecture – the Memory-Based Cognitive (MBC) architecture – based upon these considerations for the autonomous development of control of a simple mobile robot. This novel architecture will permit the exploration of theoretical issues in cognitive robotics and animal cognition. Furthermore, the biological inspiration of the architecture is anticipated to result in a mobile robot controller which displays adaptive behaviour in unknown environments.

The relationship between multi-species catch and effort: among fishery comparisons

The control of fishing mortality via fishing effort remains fundamental to most fisheries management strategies even at the local community or co-management level. Decisions to support such strategies require knowledge of the underlying response of the catch to changes in effort. Even under adaptive management strategies, imprecise knowledge of the response is likely to help accelerate the adaptive learning process. Data and institutional capacity requirements to employ multi-species biomass dynamics and age-structured models invariably render their use impractical particularly in less developed regions of the world. Surplus production models fitted to catch and effort data aggregated across all species offer viable alternatives. The current paper seeks models of this type that best describe the multi-species catch–effort responses in floodplain-rivers, lakes and reservoirs and reef-based fisheries based upon among fishery comparisons, building on earlier work. Three alternative surplus production models were fitted to estimates of catch per unit area (CPUA) and fisher density for 258 fisheries in Africa, Asia and South America. In all cases examined, the best or equal best fitting model was the Fox type, explaining up to 90% of the variation in CPUA. For lake and reservoir fisheries in Africa and Asia, the Schaefer and an asymptotic model fitted equally well. The Fox model estimates of fisher density (fishers km−2) at maximum yield (iMY) for floodplain-rivers, African lakes and reservoirs and reef-based fisheries are 13.7 (95% CI [11.8, 16.4]); 27.8 (95% CI [17.5, 66.7]) and 643 (95% CI [459,1075]), respectively and compare well with earlier estimates. Corresponding estimates of maximum yield are also given. The significantly higher value of iMY for reef-based fisheries compared to estimates for rivers and lakes reflects the use of a different measure of fisher density based upon human population size estimates. The models predict that maximum yield is achieved at a higher fishing intensity in Asian lakes compared to those in Africa. This may reflect the common practice in Asia of stocking lakes to augment natural recruitment. Because of the equilibrium assumptions underlying the models, all the estimates of maximum yield and corresponding levels of effort should be treated with caution.

Accessing biodiversity resources in computational environments from workflow applications

In the Biodiversity World (BDW) project we have created a flexible and extensible Web Services-based Grid environment for biodiversity researchers to solve problems in biodiversity and analyse biodiversity patterns. In this environment, heterogeneous and globally distributed biodiversity-related resources such as data sets and analytical tools are made available to be accessed and assembled by users into workflows to perform complex scientific experiments. One such experiment is bioclimatic modelling of the geographical distribution of individual species using climate variables in order to predict past and future climate-related changes in species distribution. Data sources and analytical tools required for such analysis of species distribution are widely dispersed, available on heterogeneous platforms, present data in different formats and lack interoperability. The BDW system brings all these disparate units together so that the user can combine tools with little thought as to their availability, data formats and interoperability. The current Web Servicesbased Grid environment enables execution of the BDW workflow tasks in remote nodes but with a limited scope. The next step in the evolution of the BDW architecture is to enable workflow tasks to utilise computational resources available within and outside the BDW domain. We describe the present BDW architecture and its transition to a new framework which provides a distributed computational environment for mapping and executing workflows in addition to bringing together heterogeneous resources and analytical tools.

Design, synthesis and computational modelling of aromatic tweezer-molecules as models for chain-folding polymer blends

Novel 'tweezer-type' complexes that exploit the interactions between pi-electron-rich pyrenyl groups and pi-electron deficient diimide units have been designed and synthesised. The component molecules leading to complex formation were accessed readily from commercially available starting materials through short and efficient syntheses. Analysis of the resulting complexes, using the visible charge-transfer band, revealed association constants that increased sequentially from 130 to 11,000 M-1 as increasing numbers of pi-pi-stacking interactions were introduced into the systems. Computational modelling was used to analyse the structures of these complexes, revealing low-energy chain-folded conformations for both components, which readily allow close, multiple pi-pi-stacking and hydrogen bonding to be achieved. In this paper, we give details of our initial studies of these complexes and outline how their behaviour could provide a basis for designing self-healing polymer blends for use in adaptive coating systems. (C) 2008 Elsevier Ltd. All rights reserved.

Geometrical isomers of [TEAH][Co(L-Se)(2)]center dot xH(2)O: synthesis, structural, spectroscopic and computational studies

Trans-1, [HNEt3][Co-III(L-Se)(2)]center dot H2O and cis-1, [HNEt3][Co-III(L-Se)(2)]center dot 3H(2)O have been synthesized and characterized by single-crystal X-ray studies. The counter ion Et3NH+ plays a crucial role in the crystal packing leading to the formation of two distinctly different supramolecular assemblies in the two complexes. In trans-1, Co-bisphenolate units and triethylamine molecules are arranged in a linear fashion leading to a supramolecular columnar assembly along the crystallographic a-axis. In this assembly, triethylammonium ions are sandwiched between successive Co-bisphenolate units and act as gluing agents joining Co-bisphenolate units on either side through C-H center dot center dot center dot pi interactions. In sharp contrast to trans-1, Co-bisphenolate units and triethylammonium ions in cis-1 are arranged in a helical supramolecular assembly through similar C-H center dot center dot center dot pi interactions along the crystallographic b-axis. The Se center dot center dot center dot Se van der Waals interactions may be responsible for the predominant occurrence of the cis-isomer. The cyclic voltammetric studies showed quasi-reversible waves for the cobalt(III) -> cobalt(II) reductions with E-1/2 = 0.635 and 0.628 V vs. Ag/AgCl for cis-1 (at similar to 5 degrees C) and trans-1 (at similar to 25 degrees C), respectively. DFT calculations show that the trans-form is the thermodynamic product with higher stability than the cis-one, which is consistent with the variable temperature H-1 NMR studies