Introduction to the Special Section on 3DTV

Cataloged from PDF version of article.The set of six papers that we invited to this part of the Special Section present extensive reviews of the state-of-the-art in functional building blocks of 3DTV systems

Learning in Multi-Agent Information Systems - A Survey from IS Perspective

Multiagent systems (MAS), long studied in artificial intelligence, have recently become popular in mainstream IS research. This resurgence in MAS research can be attributed to two phenomena: the spread of concurrent and distributed computing with the advent of the web; and a deeper integration of computing into organizations and the lives of people, which has led to increasing collaborations among large collections of interacting people and large groups of interacting machines. However, it is next to impossible to correctly and completely specify these systems a priori, especially in complex environments. The only feasible way of coping with this problem is to endow the agents with learning, i.e., an ability to improve their individual and/or system performance with time. Learning in MAS has therefore become one of the important areas of research within MAS. In this paper we present a survey of important contributions made by IS researchers to the field of learning in MAS, and present directions for future research in this area

Co atoms on Bi2_{2}Se3_{3} revealing a coverage dependent spin reorientation transition

We investigate Co nanostructures on Bi$_{2}$Se$_{3}$ by means of scanning tunneling microscopy and spectroscopy [STM/STS], X-ray absorption spectroscopy [XAS], X-ray magnetic dichroism [XMCD] and calculations using the density functional theory [DFT]. In the single adatom regime we find two different adsorption sites by STM. Our calculations reveal these to be the fcc and hcp hollow sites of the substrate. STS shows a pronounced peak for only one species of the Co adatoms indicating different electronic properties of both types. These are explained on the basis of our DFT calculations by different hybridizations with the substrate. Using XMCD we find a coverage dependent spin reorientation transition from easy-plane toward out-of-plane. We suggest clustering to be the predominant cause for this observation.Comment: 10 pages, 4 figure

Spin excitations used to probe the nature of the exchange coupling in the magnetically ordered ground state of Pr0.5_{0.5}Ca0.5_{0.5}MnO3_{3}

We have used time-of-flight inelastic neutron scattering to measure the spin wave spectrum of the canonical half-doped manganite Pr$_{0.5}$Ca$_{0.5}$MnO$_{3}$, in its magnetic and orbitally ordered phase. The data, which cover multiple Brillouin zones and the entire energy range of the excitations, are compared with several different models that are all consistent with the CE-type magnetic order, but arise through different exchange coupling schemes. The Goodenough model, i.e. an ordered state comprising strong nearest neighbor ferromagnetic interactions along zig-zag chains with antiferromagnetic inter-chain coupling, provides the best description of the data, provided that further neighbor interactions along the chains are included. We are able to rule out a coupling scheme involving formation of strongly bound ferromagnetic dimers, i.e. Zener polarons, on the basis of gross features of the observed spin wave spectrum. A model with weaker dimerization reproduces the observed dispersion but can be ruled out on the basis of discrepancies between the calculated and observed structure factors at certain positions in reciprocal space. Adding further neighbor interactions results in almost no dimerization, i.e. recovery of the Goodenough model. These results are consistent with theoretical analysis of the degenerate double exchange model for half-doping, and provide a recipe for how to interpret future measurements away from half-doping, where degenerate double exchange models predict more complex ground states.Comment: 14 pages, 11 figure

Assessment of Adaptability of a Supply Chain Trading Agent’s Strategy: Evolutionary Game Theory Approach

With the increase in the complexity of supply chain management, the use of intelligent agents for automated trading has gained popularity (Collins, Arunachalam, B, et al. 2006). The performance of supply-chain agents depends on not just the market environment (supply and demand patterns) but also on what types of other agents they are competing with. For designers of such agents it is important to ascertain that their agents are robust and can adapt to changing market and competitive environments. However, to date there has not been any work done that assesses the adaptability of a trading agent’s strategy in the presence of various demand and supply distributions when competing with a changing composition of agents using different strategies. In this paper we use the concept of replicator dynamics to study the evolution of a population of strategies used by supply chain agents when the different agents are competing against each other. We also study the evolution of the population of agents’ strategies in the presence of six types of adverse market conditions. In particular we test three strategies that have been presented in the literature and our results indicate that over time supply chain agents gravitate towards using the SCMaster strategy in most scenarios