816 resultados para Learning in multi-agent systems
Resumo:
The pituitary adenylate cyclase activating polypeptide (PACAP) type I receptor (PAC1) is a G-protein-coupled receptor binding the strongly conserved neuropeptide PACAP with 1000-fold higher affinity than the related peptide vasoactive intestinal peptide. PAC1-mediated signaling has been implicated in neuronal differentiation and synaptic plasticity. To gain further insight into the biological significance of PAC1-mediated signaling in vivo, we generated two different mutant mouse strains, harboring either a complete or a forebrain-specific inactivation of PAC1. Mutants from both strains show a deficit in contextual fear conditioning, a hippocampus-dependent associative learning paradigm. In sharp contrast, amygdala-dependent cued fear conditioning remains intact. Interestingly, no deficits in other hippocampus-dependent tasks modeling declarative learning such as the Morris water maze or the social transmission of food preference are observed. At the cellular level, the deficit in hippocampus-dependent associative learning is accompanied by an impairment of mossy fiber long-term potentiation (LTP). Because the hippocampal expression of PAC1 is restricted to mossy fiber terminals, we conclude that presynaptic PAC1-mediated signaling at the mossy fiber synapse is involved in both LTP and hippocampus-dependent associative learning.
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A contemporary perspective on the tradeoff between transmit antenna diversity andspatial multiplexing is provided. It is argued that, in the context of most modern wirelesssystems and for the operating points of interest, transmission techniques that utilizeall available spatial degrees of freedom for multiplexing outperform techniques that explicitlysacrifice spatial multiplexing for diversity. In the context of such systems, therefore,there essentially is no decision to be made between transmit antenna diversity and spatialmultiplexing in MIMO communication. Reaching this conclusion, however, requires thatthe channel and some key system features be adequately modeled and that suitable performancemetrics be adopted; failure to do so may bring about starkly different conclusions. Asa specific example, this contrast is illustrated using the 3GPP Long-Term Evolution systemdesign.
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Multi-national societies present a complex setting for the politics of immigration, as migration’s linguistic, economic and cultural effects may coincide with existing contestation over nationhood between sub-units and the central state. Empirically, though, political actors only sometimes, and in some places, explicitly connect the politics of immigration to the stakes of multi-level politics. With reference to Canada, Belgium and the United Kingdom, this paper examines the conditions under which political leaders link immigration to ongoing debate about governance in multi-national societies. The paper argues that the distribution of policy competencies in the multi-level system is less important for shaping immigration and integration politics than is the perceived impact (positive or negative) on the sub-unit’s societal culture or its power relationship with the center. Immigration and integration are more often politicized where center and sub-unit hold divergent views on migration and its place in national identity.
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Introduction: We launched an investigator-initiated study (ISRCTN31181395) to evaluate the potential benefit of pharmacokinetic-guided dosage individualization of imatinib for leukaemiapatients followed in public and private sectors. Following approval by the research ethics committee (REC) of the coordinating centre, recruitment throughout Switzerland necessitatedto submit the protocol to 11 cantonal RECs.Materials and Methods: We analysed requirements and evaluation procedures of the 12 RECs with associated costs.Results: 1-18 copies of the dossier, in total 4300 printed pages, were required (printing/posting costs: ~300 CHF) to meet initial requirements. Meeting frequencies of RECs ranged between 2 weeks and 2 months, time from submission to fi rst feedback took 2-75 days. Study approval was obtained from a chairman, a subor the full committee, the evaluation work being invoiced by0-1000 CHF (median: 750 CHF, total: 9200 CHF). While 5 RECs gave immediate approval, the other 6 rose in total 38 queries before study release, mainly related to wording in the patient information, leading to 7 different fi nal versions approved. Submission tasks employed an investigator half-time over about 6 months.Conclusion: While the necessity of clinical research evaluation by independent RECs is undisputed, there is a need of further harmonization and cooperation in evaluation procedures. Current administrative burden is indeed complex, time-consuming and costly. A harmonized electronic application form, preferably compatible with other regulatory bodies and European countries, could increase transparency, improve communication, and encourage academic multi-centre clinical research in Switzerland.
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This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.
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Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.
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We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.
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In this work I study the stability of the dynamics generated by adaptivelearning processes in intertemporal economies with lagged variables. Iprove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.
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This paper describes a bibliographic analysis of the vision of Marshal McLuhan and the vision adopted by diverse current authors regarding the use of new interactive learning technologies. The paper also analyzes the transformation that will have to take place in the formal surroundings of education in order to improve their social function. The main points of view and contributions made by diverse authors are discussed. It is important that all actors involved in the educational process take in consideration these contributions in order to be ready for future changes.
Resumo:
Inbreeding adversely affects life history traits as well as various other fitness-related traits, but its effect on cognitive traits remains largely unexplored, despite their importance to fitness of many animals under natural conditions. We studied the effects of inbreeding on aversive learning (avoidance of an odour previously associated with mechanical shock) in multiple inbred lines of Drosophila melanogaster derived from a natural population through up to 12 generations of sib mating. Whereas the strongly inbred lines after 12 generations of inbreeding (0.75<F<0.93) consistently showed reduced egg-to-adult viability (on average by 28%), the reduction in learning performance varied among assays (average=18% reduction), being most pronounced for intermediate conditioning intensity. Furthermore, moderately inbred lines (F=0.38) showed no detectable decline in learning performance, but still had reduced egg-to-adult viability, which indicates that overall inbreeding effects on learning are mild. Learning performance varied among strongly inbred lines, indicating the presence of segregating variance for learning in the base population. However, the learning performance of some inbred lines matched that of outbred flies, supporting the dominance rather than the overdominance model of inbreeding depression for this trait. Across the inbred lines, learning performance was positively correlated with the egg-to-adult viability. This positive genetic correlation contradicts a trade-off observed in previous selection experiments and suggests that much of the genetic variation for learning is owing to pleiotropic effects of genes affecting functions related to survival. These results suggest that genetic variation that affects learning specifically (rather than pleiotropically through general physiological condition) is either low or mostly due to alleles with additive (semi-dominant) effects.
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No-tillage systems, associated to black oat as preceding cover crop, have been increasingly adopted. This has motivated anticipated maize nitrogen fertilization, transferring it from the side-dress system at the stage when plants have five to six expanded leaves to when the preceding cover crop is eliminated or to maize sowing. This study was conducted to evaluate the effects of soil tillage system and timing of N fertilization on maize grain yield and agronomic efficiency of N applied to a soil with high organic matter content. A three-year field experiment was conducted in Lages, state of Santa Catarina, from 1999 onwards. Treatments were set up in a split plot arrangement. Two soil tillage systems were tested in the main plots: conventional tillage (CT) and no-tillage (NT). Six N management systems were assessed in the split-plots: S1 - control, without N application; S2 - all N (100 kg ha-1) applied at oat desiccation; S3 - all N applied at maize sowing; S4 - all N side-dressed when maize had five expanded leaves (V5 growth stage); S5 - 1/3 of N rate applied at maize sowing and 2/3 at V5; S6 - 2/3 of nitrogen rate applied at maize sowing and 1/3 at V5. Maize response to the time and form of splitting N was not affected by the soil tillage system. Grain yield ranged from 6.0 to 11.8 t ha-1. The anticipation of N application (S2 and S3) decreased grain yield in two of three years. In the rainiest early spring season (2000/2001) of the experiment, S4 promoted an yield advantage of 2.2 t ha-1 over S2 and S3. Application of total N rate before or at sowing decreased the number of kernels produced per ear in 2000/2001 and 2001/2002 and the number of ears produced per area in 2001/2002, resulting in reduced grain yield. The agronomic efficiency of applied N (kg grain increase/kg of N applied) ranged from 13.9 to 38.8 and was always higher in the S4 than in the S2 and S3 N systems. Short-term N immobilization did not reduce grain yield when no N was applied before or at maize sowing in a soil with high organic matter content, regardless of the soil tillage system.