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Issue linkage is often advocated as a powerful mechanism to encourage cooperation on issues where free-riding incentives are significant. The basic idea is to link cooperation on such issues with cooperation on issues that provide (partially) excludable benefits and are therefore less susceptible to free-riding. In this paper, we take a coalition formation approach and study the effects of issue linkage on overall cooperation levels and welfare. We show that, when the linked issues are independent, issue linkage is not necessarily welfare improving; in fact, unless the less critical issue is almost perfectly excludable, issue linkage leads to a welfare loss. By contrast, a generalized enlargement of cooperation and an increase in welfare are obtainable when the linked issues are "complements". Using concepts from network theory, we further provide insights into the design of cost-effective (minimally connected) linkage architectures when more than two issues are at stake. [ABSTRACT FROM AUTHOR]

This paper examines experimentally how reputational uncertainty and the rate of change of the social environment determine cooperation. Reputational uncertainty significantly decreases cooperation, while a fast-changing social environment only causes a second-order qualitative increase in cooperation. At the individual level, reputational uncertainty induces more leniency and forgiveness in imposing network punishment through the link proposal and removal processes, inhibiting the formation of cooperative clusters. However, this effect is significant only in the fast-changing environment and not in the slow-changing environment. A substitution pattern between network punishment and action punishment (retaliatory defection) explains this discrepancy across the two social environments. [ABSTRACT FROM AUTHOR]

We consider a fixed network of players endowed with idiosyncratic preferences over actions and involved in interactions of various types. The aim is to investigate the interplay between idiosyncratic preferences and interactional incentives on a network. The earlier literature demonstrated the conflict between players' intrinsic preferences and coordination incentives. This paper shows that such a conflict is also present in contexts in which players do not necessarily aim at coordination with their peers. The introduction of action preferences changes equilibrium outcomes in a non-trivial fashion: some equilibria disappear, while other, qualitatively new ones, appear. We characterize equilibria for a large class of games, including games of strategic complements and strategic substitutes, and outline a subclass with a unique equilibrium in which all players follow their idiosyncratic action preferences. This equilibrium is Pareto optimal and for many games is also a unique efficient profile. [ABSTRACT FROM AUTHOR]

Several approaches and techniques exist to resolve load balancing problem in general and torus topology networks. Graph methods are natural ways to perform balancing of routing paths. A routing balancing algorithm must operate within the constraints of the underlying network architecture that limits several parameters, such as the number of logical paths in the network. In this paper, we consider a torus topology that is one of the common topologies that are used in high performance computing systems. We introduce a routing graph that corresponds to a interconnect topology, abstracts interconnect routing rules, providing one-to-one correspondence of network routes and graph paths. We propose a deadlock-free routing algorithm based on a fast single-source shortest path algorithm in a routing graph for the deterministic routing of a torus topology interconnect with a single virtual channel. The proposed algorithm is a tradeoff between two existing routing algorithms, also the algorithm is optimized for multidimensional torus topology and can be applied to any torus topology HPC system. We present a complete description of a routing graph that abstracts the Angara interconnect with 4D torus topology. We evaluated the proposed routing algorithm and benchmarked the maximum performance improvement of 71% for the Alltoall pattern for torus topology systems up to 432 nodes on the Angara interconnect simulator. The performance improvement of more than 5% was obtained for the NPB FT and IS application kernels on a 32-node supercomputer. • A routing graph abstracts network routing rules. • A deadlock-free routing algorithm is based on a fast single-source shortest path algorithm and optimized for a torus topology. • A routing graph for the Angara network reflects the restrictions on a further packet route with the previous route steps in mind. • The maximum performance improvement is 71% for the Alltoall pattern on the simulated torus topology systems up to 432 nodes. • The performance improvement on the 32-node Angara based cluster is 5% for the NPB FT and IS application kernels. [ABSTRACT FROM AUTHOR]

This paper describes and validates a novel framework using the Approximate Bayesian Computation (ABC) algorithm for parameter estimation and model selection in models of mesoscale brain network activity. We provide a proof of principle, first pass validation of this framework using a set of neural mass models of the cortico-basal ganglia thalamic circuit inverted upon spectral features from experimental, in vivo recordings. This optimization scheme relaxes an assumption of fixed-form posteriors (i.e. the Laplace approximation) taken in previous approaches to inverse modelling of spectral features. This enables the exploration of model dynamics beyond that approximated from local linearity assumptions and so fit to explicit, numerical solutions of the underlying non-linear system of equations. In this first paper, we establish a face validation of the optimization procedures in terms of: (i) the ability to approximate posterior densities over parameters that are plausible given the known causes of the data; (ii) the ability of the model comparison procedures to yield posterior model probabilities that can identify the model structure known to generate the data; and (iii) the robustness of these procedures to local minima in the face of different starting conditions. Finally, as an illustrative application we show (iv) that model comparison can yield plausible conclusions given the known neurobiology of the cortico-basal ganglia-thalamic circuit in Parkinsonism. These results lay the groundwork for future studies utilizing highly nonlinear or brittle models that can explain time dependant dynamics, such as oscillatory bursts, in terms of the underlying neural circuits. [ABSTRACT FROM AUTHOR]