Advances in Complex Systems

Trust models play an important role in computational environments. One of the main aims of the work undertaken in this domain is to provide a model that can better describe the socio-technical nature of computational trust. It has been recently shown that quantum-like formulations in the field of human decision making can better explain the underlying nature of these types of processes. Based on this research, the aim of this paper is to propose a novel model of trust based on quantum probabilities as the underlying mathematics of quantum theory. It will be shown that by using this new mathematical framework, we will have a powerful mechanism to model the contextuality property of trust. Also, it is hypothesized that many events or evaluations in the context of trust can be and should be considered as incompatible, which is unique to the noncommutative structure of quantum probabilities. The main contribution of this paper will be that, by using the quantum Bayesian inference mechanism for belief updating in the framework of quantum theory, we propose a biased trust inference mechanism. This mechanism allows us to model the negative and positive biases that a trustor may subjectively feel toward a certain trustee candidate. It is shown that by using this bias, we can model and describe the exploration versus exploitation problem in the context of trust decision making, recency effects for recently good or bad transactions, filtering pessimistic and optimistic recommendations that may result in good-mouthing or bad-mouthing attacks, the attitude of the trustor toward risk and uncertainty in different situations and the pseudo-transitivity property of trust. Finally, we have conducted several experimental evaluations in order to demonstrate the effectiveness of the proposed model in different scenarios.

An analytical treatment of a simple opinion model with contrarian behavior is presented. The focus is on the stationary dynamics of the model and in particular on the effect of inhomogeneities in the interaction topology on the stationary behavior. We start from a micro-level Markov chain description of the model. Markov chain aggregation is then used to derive a macro chain for the complete graph as well as a meso-level description for the two-community graph composed of two (weakly) coupled sub-communities. In both cases, a detailed understanding of the model behavior is possible using Markov chain tools. More importantly, however, this setting provides an analytical scenario to study the discrepancy between the homogeneous mixing case and the model on a slightly more complex topology. We show that memory effects are introduced at the macro-level when we aggregate over agent attributes without sensitivity to the microscopic details and quantify these effects using concepts from information theory. In this way, the method facilitates the analysis of the relation between microscopic processes and their aggregation to a macroscopic level of description and informs about the complexity of a system introduced by heterogeneous interaction relations.

Recovery of society after a large-scale disaster generally consists of two phases, short- and long-term recoveries. The main goal of the short-term recovery is to bounce the damaged system back to the operating standards enabling residents in damaged cities to survive, and fast supply with vital resources to them is one of its important elements. We propose a general principle by which the required redistribution of vital resources between the affected and neighboring cities can be efficiently implemented. The short-term recovery is a rescuer operation where uncertainty in evaluating the state of damaged region is highly probable. To allow for such an operation, the developed principle involves two basic components. The first one of ethic nature is the triage concept determining the current city priority in the resource delivery. The second one is the minimization of the delivery time subjected to this priority. Finally a certain plan of the resource redistribution is generated according to this principle. Several specific examples are studied numerically. It elucidates, in particular, the effects of system characteristics such as the city limit capacity in resource delivery, the type of initial resource allocation among the cities, the number of cities able to participate in the resource redistribution, and the damage level in the affected cities. As far as the uncertainty in evaluating the state of damaged region is concerned, some specific cases were studied. It assumes the initial communication system has crashed and formation of a new one and the resource redistribution proceed synchronously. The obtained results enable us to consider the resource redistribution plan governed by the proposed method semi-optimal and rather efficient especially under uncertainty.