Risk-bounded formation of fuzzy coalitions among service agents.

Cooperative autonomous agents form coalitions in order ro share and combine resources and services to efficiently respond to market demands. With the variety of resources and services provided online today, there is a need for stable and flexible techniques to support the automation of agent coalition formation in this context. This paper describes an approach to the problem based on fuzzy coalitions. Compared with a classic cooperative game with crisp coalitions (where each agent is a full member of exactly one coalition), an agent can participate in multiple coalitions with varying degrees of involvement. This gives the agent more freedom and flexibility, allowing them to make full use of their resources, thus maximising utility, even if only comparatively small coalitions are formed. An important aspect of our approach is that the agents can control and bound the risk caused by the possible failure or default of some partner agents by spreading their involvement in diverse coalitions

An Ordinal Approach to Risk Measurement

In this short note, we aim at a qualitative framework for modeling multivariate risk. To this extent, we consider completely distributive lattices as underlying universes, and make use of lattice functions to formalize the notion of risk measure. Several properties of risk measures are translated into this general setting, and used to provide axiomatic characterizations. Moreover, a notion of quantile of a lattice-valued random variable is proposed, which shown to retain several desirable properties of its real-valued counterpart.lattice; risk measure; Sugeno integral; quantile.

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

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Evaluating Capital Allocation Below Portfolio Level

This thesis explores the ability for retail banks to allocate economic capital below portfolio level. First, a discussion about capital requirements and risk measures to provide a sound basis for determining the economic capital of the bank. In general, economic capital is allocated to the banks portfolios but not on a more granular level, through a capital allocation method. This study discuss three dierent approaches for allocation of economic capital below portfolio level; game theory, nance and optimization. Both the game theory and nance approach reach the same conclusion, that the best allocation principle is the gradient of the risk measure. The optimization method allocates economic capital through minimization of a concept called risk residual, which conclude that the optimal allocation is derived from the marginal distribution of a customer. Capital allocation below portfolio level give the management a good overview of risks from dierent customers. In order to determine the performance of the portfolios in the bank a Risk-Adjusted-Return-On-Capital is used, with economic capital as input. The thesis include some comments about how the choice of capital allocation methods aect the performance measurement. The thesis concludes with an evaluation of the methods by simulations of a ctional bank conducted in the software R. Key Words: Risk Appetite, Economic Capital, Risk measure, Capital Allocation Methods, Allocation Below Portfolio level, Game theory, Optimization, Marginal Contributio

The norm-1-property of a quantum observable

A normalized positive operator measure $X\mapsto E(X)$ has the norm-1-property if \no{E(X)}=1 whenever $E(X)\ne O$. This property reflects the fact that the measurement outcome probabilities for the values of such observables can be made arbitrary close to one with suitable state preparations. Some general implications of the norm-1-property are investigated. As case studies, localization observables, phase observables, and phase space observables are considered.Comment: 14 page

Mutual synchronization and clustering in randomly coupled chaotic dynamical networks

We introduce and study systems of randomly coupled maps (RCM) where the relevant parameter is the degree of connectivity in the system. Global (almost-) synchronized states are found (equivalent to the synchronization observed in globally coupled maps) until a certain critical threshold for the connectivity is reached. We further show that not only the average connectivity, but also the architecture of the couplings is responsible for the cluster structure observed. We analyse the different phases of the system and use various correlation measures in order to detect ordered non-synchronized states. Finally, it is shown that the system displays a dynamical hierarchical clustering which allows the definition of emerging graphs.Comment: 13 pages, to appear in Phys. Rev.

Community Detection in Quantum Complex Networks

Determining community structure is a central topic in the study of complex networks, be it technological, social, biological or chemical, in static or interacting systems. In this paper, we extend the concept of community detection from classical to quantum systems---a crucial missing component of a theory of complex networks based on quantum mechanics. We demonstrate that certain quantum mechanical effects cannot be captured using current classical complex network tools and provide new methods that overcome these problems. Our approaches are based on defining closeness measures between nodes, and then maximizing modularity with hierarchical clustering. Our closeness functions are based on quantum transport probability and state fidelity, two important quantities in quantum information theory. To illustrate the effectiveness of our approach in detecting community structure in quantum systems, we provide several examples, including a naturally occurring light-harvesting complex, LHCII. The prediction of our simplest algorithm, semiclassical in nature, mostly agrees with a proposed partitioning for the LHCII found in quantum chemistry literature, whereas our fully quantum treatment of the problem uncovers a new, consistent, and appropriately quantum community structure.Comment: 16 pages, 4 figures, 1 tabl

Managed information gathering and fusion for transient transport problems

This paper deals with vehicular traffic management by communication technologies from Traffic Control Center point of view in road networks. The global goal is to manage the urban traffic by road traffic operations, controlling and interventional possibilities in order to minimize the traffic delays and stops and to improve traffic safety on the roads. This paper focuses on transient transport, when the controlling management is crucial. The aim was to detect the beginning time of the transient traffic on the roads, to gather the most appropriate data and to get reliable information for interventional suggestions. More reliable information can be created by information fusion, several fusion techniques are expounded in this paper. A half-automatic solution with Decision Support System has been developed to help with engineers in suggestions of interventions based on real time traffic data. The information fusion has benefits for Decision Support System: the complementary sensors may fill the gaps of one another, the system is able to detect the changing of the percentage of different vehicle types in traffic. An example of detection and interventional suggestion about transient traffic on transport networks of a little town is presented at the end of the paper. The novelty of this paper is the gathering of information - triggered by the state changing from stationer to transient - from ad hoc channels and combining them with information from developed regular channels. --information gathering,information fusion,Kalman filter,transient traffic,Decision Support System