Public statistics and private experience: varying feedback information in a take or pass game

We study how subjects in an experiment use different forms of public information about their opponents’ past behaviour. In the absence of public information, subjects appear to use rather detailed statistics summarizing their private experiences. If they have additional public information, they make use of this information even if it is less precise than their own private statistics–except for very high stakes. Making public information more precise has two consequences: It is also used when the stakes are very high and it reduces the number of subjects who ignore any information–public and private. That is, precise public information crowds in the use of own information. Finally, our results shed some light on unravelling in centipede games

Endogenous leadership in teams

In this paper we study the mechanics of “leading by example” in teams. Leadership is beneficial for the entire team when agents are conformists, i.e., dislike effort differentials. We also show how leadership can arise endogenously and discuss what type of leader benefits a team most

Learning spillover and analogy-based expectations: a multi-game experiment

We consider a multi-game interactive learning environment and ask ourselves whether long run behaviors in one game are a¤ected by behaviors in the other, i.e whether there are learning spillovers. Our main �nding is that learning spillovers arise whenever the feedback provided to subjects about past play is not easily accessible game by game and thus subjects get a more immediate impression about aggregate distributions. In such a case, long run behaviors stabilize to an analogy-based expectation equilibrium (Jehiel 2005), thereby suggesting how one should broaden the notion of equilibrium to cope with learning spillovers

Magic numbers in the discrete tomography of cyclotomic model sets

We report recent progress in the problem of distinguishing convex subsets of cyclotomic model sets $\varLambda$ by (discrete parallel) X-rays in prescribed $\varLambda$-directions. It turns out that for any of these model sets $\varLambda$ there exists a `magic number' $m_{\varLambda}$ such that any two convex subsets of $\varLambda$ can be distinguished by their X-rays in any set of $m_{\varLambda}$ prescribed $\varLambda$-directions. In particular, for pentagonal, octagonal, decagonal and dodecagonal model sets, the least possible numbers are in that very order 11, 9, 11 and 13.Comment: 6 pages, 1 figure; based on the results of arXiv:1101.4149 [math.MG]; presented at Aperiodic 2012 (Cairns, Australia

Niveaux d'énergie de 28Si au voisinage de 13,245 MeV observés à l'aide des réactions 27Al(p, γ)28Si et 27Al(p, α) 24Mg

L'étude simultanée des caractéristiques des résonances de la réaction 27Al + p à une énergie Ep = 1 724 keV, pour différentes voies de sortie, a permis de conclure à l'existence de deux niveaux distincts (Jπ = 3-, Jπ = 5-) dans 28Si situés à 13 245 ± 2 keV

Simulation-based Testing for Early Safety-Validation of Robot Systems

Industrial human-robot collaborative systems must be validated thoroughly with regard to safety. The sooner potential hazards for workers can be exposed, the less costly is the implementation of necessary changes. Due to the complexity of robot systems, safety flaws often stay hidden, especially at early design stages, when a physical implementation is not yet available for testing. Simulation-based testing is a possible way to identify hazards in an early stage. However, creating simulation conditions in which hazards become observable can be difficult. Brute-force or Monte-Carlo-approaches are often not viable for hazard identification, due to large search spaces. This work addresses this problem by using a human model and an optimization algorithm to generate high-risk human behavior in simulation, thereby exposing potential hazards. A proof of concept is shown in an application example where the method is used to find hazards in an industrial robot cell

Relationship between moonlight and nightly activity patterns of the ocelot (Leopardus pardalis) and some of its prey species in Formosa, Northern Argentina

The moon can profoundly influence the activity patterns of animals. If predators are more successful under bright moonlight, prey species are likely to respond by shifting their own activity patterns (predator-avoidance hypothesis). However, the assumption that prey will necessarily avoid full-moon nights does not take into account that moonlight also allows prey to more easily detect predators, and to forage more efficiently. Thus, nightly activity patterns could depend on night vision capabilities (visual-acuity hypothesis). To consider the possible influences of moonlight and to distinguish between these hypotheses, we used camera-trapping records of a predator, the ocelot (Leopardus pardalis), and several of its night-active prey to compare activity patterns under different moonlight conditions. The ocelots' activity patterns were not strongly related to moonlight, but showed a slight tendency for higher activity during brighter nights. Tapeti rabbits (Sylvilagus brasiliensis) and brocket deer (Mazama americana) showed a clear preference for brighter nights. White-eared opossums (Didelphis albiventris) also showed a trend to be less active in new moon light. In contrast, smaller grey four-eyed opossums (Philander opossum) and the poor eye-sight nine-banded armadillo (Dasypus novemcinctus) showed similar activity patterns across all moon phases. Since activity patterns of most prey species were not shifted away from the activity of the ocelot, the differences between species are probably linked to their night vision capabilities, and emphasise the need for more information on the visual system of these taxa. Their activity patterns seem to be less strongly linked to avoidance of predation than previously thought, suggesting that foraging and predator detection benefits may play a more important role than usually acknowledged.The cameras were partly funded by a National Geographic Society/Waitt grant to MH (grant number NGS 1072-78) and partly by quality-related funding through the Research Excellence Framework to the Biological Sciences Research Group of the University of Derby. The long-term camera-trap monitoring was in part made possible through grants to EFD and the Owl Monkey Project from the L.S.B. Leakey Foundation, National Geographic Society and the National Science Foundation of the USA (NSF-BCS-0621020, 0837921 (REU), 0924352 (REU), 1026991 (REU), 1219368 (RAPID) and 1232349 (2012)