Budget processes : theory and experimental evidence

This paper studies budget processes, both theoretically and experimentally. We give a sufficient condition for top-down and bottom-up budget processes to have the same voting equilibrium. Furthermore, at a voting equilibrium, it is not always true, as often presumed, that a top-down budget process leads to a smaller overall budget than does a bottom-up budget process. To test the implications for budget processes of voting equilibrium theory, we conduct a series of 128 voting experiments using subjects in a behavior laboratory. The experimental evidence from these experiments is well organized by voting equilibrium theory, both at the aggregate level and at the individual subject level. In particular, subjects display considerable evidence of rationality in their proposals and votes. More complete information and fewer spending categories lead to greater predictive success of voting equilibrium theory, and reduce the time needed to reach a budget decision

Budget Processes: Theory and Experimental Evidence

This paper studies budget processes, both theoretically and experimentally. We compare the outcomes of bottom-up and top-down budget processes. It is often presumed that a top-down budget process leads to a smaller overall budget than a bottom-up budget process. Ferejohn and Krehbiel (1987) showed theoretically that this need not be the case. We test experimentally the theoretical predictions of their work. The evidence from these experiments lends strong support to their theory, both at the aggregate and the individual subject level

Typical properties of optimal growth in the Von Neumann expanding model for large random economies

We calculate the optimal solutions of the fully heterogeneous Von Neumann expansion problem with $N$ processes and $P$ goods in the limit $N\to\infty$. This model provides an elementary description of the growth of a production economy in the long run. The system turns from a contracting to an expanding phase as $N$ increases beyond $P$. The solution is characterized by a universal behavior, independent of the parameters of the disorder statistics. Associating technological innovation to an increase of $N$, we find that while such an increase has a large positive impact on long term growth when $N\ll P$, its effect on technologically advanced economies ($N\gg P$) is very weak.Comment: 8 pages, 1 figur

Coarse-graining of cellular automata, emergence, and the predictability of complex systems

We study the predictability of emergent phenomena in complex systems. Using nearest neighbor, one-dimensional Cellular Automata (CA) as an example, we show how to construct local coarse-grained descriptions of CA in all classes of Wolfram's classification. The resulting coarse-grained CA that we construct are capable of emulating the large-scale behavior of the original systems without accounting for small-scale details. Several CA that can be coarse-grained by this construction are known to be universal Turing machines; they can emulate any CA or other computing devices and are therefore undecidable. We thus show that because in practice one only seeks coarse-grained information, complex physical systems can be predictable and even decidable at some level of description. The renormalization group flows that we construct induce a hierarchy of CA rules. This hierarchy agrees well with apparent rule complexity and is therefore a good candidate for a complexity measure and a classification method. Finally we argue that the large scale dynamics of CA can be very simple, at least when measured by the Kolmogorov complexity of the large scale update rule, and moreover exhibits a novel scaling law. We show that because of this large-scale simplicity, the probability of finding a coarse-grained description of CA approaches unity as one goes to increasingly coarser scales. We interpret this large scale simplicity as a pattern formation mechanism in which large scale patterns are forced upon the system by the simplicity of the rules that govern the large scale dynamics.Comment: 18 pages, 9 figure

Analysis of Oscillator Neural Networks for Sparsely Coded Phase Patterns

We study a simple extended model of oscillator neural networks capable of storing sparsely coded phase patterns, in which information is encoded both in the mean firing rate and in the timing of spikes. Applying the methods of statistical neurodynamics to our model, we theoretically investigate the model's associative memory capability by evaluating its maximum storage capacities and deriving its basins of attraction. It is shown that, as in the Hopfield model, the storage capacity diverges as the activity level decreases. We consider various practically and theoretically important cases. For example, it is revealed that a dynamically adjusted threshold mechanism enhances the retrieval ability of the associative memory. It is also found that, under suitable conditions, the network can recall patterns even in the case that patterns with different activity levels are stored at the same time. In addition, we examine the robustness with respect to damage of the synaptic connections. The validity of these theoretical results is confirmed by reasonable agreement with numerical simulations.Comment: 23 pages, 11 figure

Optics-less smart sensors and a possible mechanism of cutaneous vision in nature

Optics-less cutaneous (skin) vision is not rare among living organisms, though its mechanisms and capabilities have not been thoroughly investigated. This paper demonstrates, using methods from statistical parameter estimation theory and numerical simulations, that an array of bare sensors with a natural cosine-law angular sensitivity arranged on a flat or curved surface has the ability to perform imaging tasks without any optics at all. The working principle of this type of optics-less sensor and the model developed here for determining sensor performance may be used to shed light upon possible mechanisms and capabilities of cutaneous vision in nature

“No research on a dead planet”: preserving the socio-ecological conditions for academia

Despite thousands of higher education institutions (HEIs) having issued Climate Emergency declarations, most academics continue to operate according to ‘business-as-usual’. However, such passivity increases the risk of climate impacts so severe as to threaten the persistence of organized society, and thus HEIs themselves. This paper explores why a maladaptive cognitive-practice gap persists and asks what steps could be taken by members of HEIs to activate the academy. Drawing on insights from climate psychology and sociology, we argue that a process of ‘socially organized denial’ currently exists within universities, leading academics to experience a state of ‘double reality’ that inhibits feelings of accountability and agency, and this is self-reenforcing through the production of ‘pluralistic ignorance.’ We further argue that these processes serve to uphold the cultural hegemony of ‘business-as-usual’ and that this is worsened by the increasing neo-liberalization of modern universities. Escaping these dynamics will require deliberate efforts to break taboos, through frank conversations about what responding to a climate emergency means for universities’ – and individual academics’ – core values and goals

Herbert Simon's decision-making approach: Investigation of cognitive processes in experts

This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment

The Calar Alto Deep Imaging Survey: K-band Galaxy Number Counts

We present K-band number counts for the faint galaxies in the Calar Alto Deep Imaging Survey (CADIS). We covered 4 CADIS fields, a total area of 0.2deg^2, in the broad band filters B, R and K. We detect about 4000 galaxies in the K-band images, with a completeness limit of K=19.75mag, and derive the K-band galaxy number counts in the range of 14.25 < K < 19.75mag. This is the largest medium deep K-band survey to date in this magnitude range. The B- and R-band number counts are also derived, down to completeness limits of B=24.75mag and R=23.25mag. The K-selected galaxies in this magnitude range are of particular interest, since some medium deep near-infrared surveys have identified breaks of both the slope of the K-band number counts and the mean B-K color at K=17\sim18mag. There is, however, a significant disagreement in the K-band number counts among the existing surveys. Our large near-infrared selected galaxy sample allows us to establish the presence of a clear break in the slope at K=17.0mag from dlogN/dm = 0.64 at brighter magnitudes to dlogN/dm = 0.36 at the fainter end. We construct no-evolution and passive evolution models, and find that the passive evolution model can simultaneously fit the B-, R- and K-band number counts well. The B-K colors show a clear trend to bluer colors for K > 18mag. We also find that most of the K=18-20mag galaxies have a B-K color bluer than the prediction of a no-evolution model for an L_* Sbc galaxy, implying either significant evolution, even for massive galaxies, or the existence of an extra population of small galaxies.Comment: Accepted for A&A, 10 pages, 7 figure