Decidable model-checking for a resource logic with production of resources

Several logics for expressing coalitional ability under resource bounds have been proposed and studied in the literature. Previous work has shown that if only consumption of resources is considered or the total amount of resources produced or consumed on any path in the system is bounded, then the model-checking problem for several standard logics, such as Resource-Bounded Coalition Logic (RB-CL) and Resource-Bounded Alternating-Time Temporal Logic (RB-ATL) is decidable. However, for coalition logics with unbounded resource production and consumption, only some undecidability results are known. In this paper, we show that the model-checking problem for RB-ATL with unbounded production and consumption of resources is decidable

Symbolic model checking for one-resource RB±ATL

RB±ATL is an extension of ATL where it is possible to model consumption and production of several resources by a set of agents. The model-checking problem for RB±ATL is known to be decidable. However the only available model-checking algorithm for RB±ATL uses a forward search of the state space, and hence does not have an efficient symbolic implementation. In this paper, we consider a fragment of RB±ATL, 1RB±ATL, that allows only one resource type. We give a symbolic model-checking algorithm for this fragment of RB±ATL, and evaluate the performance of an MCMAS-based implementation of the algorithm on an example problem that can be scaled to large state spaces

Stroboscopic Research

Contains research objectives and reports on one research project

BDI agent architectures: A survey

The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach

New results for a photon-photon collider

We present new results from studies in progress on physics at a two-photon collider. We report on the sensitivity to top squark parameters of MSSM Higgs boson production in two-photon collisions; Higgs boson decay to two photons; radion production in models of warped extra dimensions; chargino pair production; sensitivity to the trilinear Higgs boson coupling; charged Higgs boson pair production; and we discuss the backgrounds produced by resolved photon-photon interactions.Comment: 17 pages, 15 figure

Application of random coherence order selection in gradient-enhanced multidimensional NMR

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2$^{N−1}$ to the number of free-induction decays which must be acquired, where $N$ is the number of dimensions. Compressed sensing (CS) ℓ$_{1}$-norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 $\small \textit{PNAS}$ 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp ($\textit{iωt}$) or exp (−$\textit{iωt}$), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ$_1$-norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended to the full suite of experiments available to modern NMR spectroscopy, allowing resolution enhancements for all indirect dimensions; alone or in combination with NUS, RQD can be used to improve experimental resolution, or shorten experiment times, of considerable benefit to the challenging applications undertaken by modern NMR.This is the final version of the article. It first appeared from IOP Publishing via http://dx.doi.org/10.1088/1742-6596/699/1/01200

Inequalities and Positive-Definite Functions Arising From a Problem in Multidimensional Scaling

We solve the following variational problem: Find the maximum of E ∥ X−Y ∥ subject to E ∥ X ∥2 ≤ 1, where X and Y are i.i.d. random n-vectors, and ∥⋅∥ is the usual Euclidean norm on Rn. This problem arose from an investigation into multidimensional scaling, a data analytic method for visualizing proximity data. We show that the optimal X is unique and is (1) uniform on the surface of the unit sphere, for dimensions n ≥ 3, (2) circularly symmetric with a scaled version of the radial density ρ/(1−ρ2)1/2, 0 ≤ ρ ≤1, for n=2, and (3) uniform on an interval centered at the origin, for n=1 (Plackett\u27s theorem). By proving spherical symmetry of the solution, a reduction to a radial problem is achieved. The solution is then found using the Wiener-Hopf technique for (real) n \u3c 3. The results are reminiscent of classical potential theory, but they cannot be reduced to it. Along the way, we obtain results of independent interest: for any i.i.d. random n-vectors X and Y,E ∥ X−Y ∥ ≤ E ∥ X+Y ∥. Further, the kernel Kp, β(x,y) = ∥ x+y ∥βp− ∥x−y∥βp, x, y∈Rn and ∥ x ∥ p=(∑|xi|p)1/p, is positive-definite, that is, it is the covariance of a random field, Kp,β(x,y) = E [ Z(x)Z(y) ] for some real-valued random process Z(x), for 1 ≤ p ≤ 2 and 0 \u3c β ≤ p ≤ 2 (but not for β \u3ep or p\u3e2 in general). Although this is an easy consequence of known results, it appears to be new in a strict sense. In the radial problem, the average distance D(r1,r2) between two spheres of radii r1 and r2 is used as a kernel. We derive properties of D(r1,r2), including nonnegative definiteness on signed measures of zero integral

Diffusion, Cell Mobility, and Bandlimited Functions

The mechanism by which leukocytes steer toward a chemical attractant is not fully resolved. Experimental data suggest that these cells detect differences in concentration of chemoattractant over their surface and walk up the gradient. The problem has been considered theoretically only in stationary media, where the distribution of attractant is determined solely by diffusion. Experimentally, bulk flow has been allowed only unintentionally. Since bulk flow is characteristic of real systems, we examine a simple two-dimensional model incorporating both diffusion and an additional drift. The latter problem leads to an integral equation which is central also in the study of weighted Hilbert spaces of bandlimited functions. We find asymptotic expressions for the required solution by a Wiener-Hopf method adapted to a finite interval. We conclude that, without drift, the concentration does not vary detectably around the cell, but that drift inceases this variation substantially. Thus over model suggests that drift may play an important role in the cell\u27s chemotactic response

Limit Distributions of Self-Normalized Sums

If Xi are i.i.d. and have zero mean and arbitrary finite variance the limiting probability distribution of Sn(2) =(∑ni=1 Xi)/(∑nj=1Xj2)1/2 as n→∞ has density f(t) = (2π)−1/2 exp(−t2/2) by the central limit theorem and the law of large numbers. If the tails of Xi are sufficiently smooth and satisfy P(Xi \u3e t) ∼ rt−α and P(Xi \u3c −t) ∼ lt−α as t→∞, where 0 \u3c α \u3c 2, r \u3e 0, l \u3e 0, Sn(2) still has a limiting distribution F even though Xi has infinite variance. The density f of F depends on α as well as on r/l. We also study the limiting distribution of the more general Sn(p) = (∑ni=1Xi)/(∑nj=1 |Xj|p)1/p where Xi are i.i.d. and in the domain of a stable law G with tails as above. In the cases p = 2 (see (4.21)) and p = 1 (see (3.7)) we obtain exact, computable formulas for f(t) = f(t,α,r/l), and give graphs of f for a number of values of α and r/l. For p = 2, we find that f is always symmetric about zero on (−1,1), even though f is symmetric on (−∞,∞) only when r = l