Why Are People's Decisions Sometimes Worse with Computer Support?

In many applications of computerised decision support, a recognised source of undesired outcomes is operators' apparent over-reliance on automation. For instance, an operator may fail to react to a potentially dangerous situation because a computer fails to generate an alarm. However, the very use of terms like "over-reliance" betrays possible misunderstandings of these phenomena and their causes, which may lead to ineffective corrective action (e.g. training or procedures that do not counteract all the causes of the apparently "over-reliant" behaviour). We review relevant literature in the area of "automation bias" and describe the diverse mechanisms that may be involved in human errors when using computer support. We discuss these mechanisms, with reference to errors of omission when using "alerting systems", with the help of examples of novel counterintuitive findings we obtained from a case study in a health care application, as well as other examples from the literature

Bayesian reinforcement learning with exploration

We consider a general reinforcement learning problem and show that carefully combining the Bayesian optimal policy and an exploring policy leads to minimax sample-complexity bounds in a very general class of (history-based) environments. We also prove lower bounds and show that the new algorithm displays adaptive behaviour when the environment is easier than worst-case

Sparticle mass spectra from SU(5) SUSY GUT models with b−τb-\tau Yukawa coupling unification

Supersymmetric grand unified models based on the gauge group SU(5) often require in addition to gauge coupling unification, the unification of b-quark and $\tau$-lepton Yukawa couplings. We examine SU(5) SUSY GUT parameter space under the condition of $b-\tau$ Yukawa coupling unification using 2-loop MSSM RGEs including full 1-loop threshold effects. The Yukawa-unified solutions break down into two classes. Solutions with low tan\beta ~3-11 are characterized by gluino mass ~1-4 TeV and squark mass ~1-5 TeV. Many of these solutions would be beyond LHC reach, although they contain a light Higgs scalar with mass <123 GeV and so may be excluded should the LHC Higgs hint persist. The second class of solutions occurs at large tan\beta ~35-60, and are a subset of $t-b-\tau$ unified solutions. Constraining only $b-\tau$ unification to ~5% favors a rather light gluino with mass ~0.5-2 TeV, which should ultimately be accessible to LHC searches. While our $b-\tau$ unified solutions can be consistent with a picture of neutralino-only cold dark matter, invoking additional moduli or Peccei-Quinn superfields can allow for all of our Yukawa-unified solutions to be consistent with the measured dark matter abundance.Comment: 19 pages, 5 figures, 1 table, PDFLate

Improving the Price of Anarchy for Selfish Routing via Coordination Mechanisms

We reconsider the well-studied Selfish Routing game with affine latency functions. The Price of Anarchy for this class of games takes maximum value 4/3; this maximum is attained already for a simple network of two parallel links, known as Pigou's network. We improve upon the value 4/3 by means of Coordination Mechanisms. We increase the latency functions of the edges in the network, i.e., if $\ell_e(x)$ is the latency function of an edge $e$, we replace it by $\hat{\ell}_e(x)$ with $\ell_e(x) \le \hat{\ell}_e(x)$ for all $x$. Then an adversary fixes a demand rate as input. The engineered Price of Anarchy of the mechanism is defined as the worst-case ratio of the Nash social cost in the modified network over the optimal social cost in the original network. Formally, if \CM(r) denotes the cost of the worst Nash flow in the modified network for rate $r$ and \Copt(r) denotes the cost of the optimal flow in the original network for the same rate then [\ePoA = \max_{r \ge 0} \frac{\CM(r)}{\Copt(r)}.] We first exhibit a simple coordination mechanism that achieves for any network of parallel links an engineered Price of Anarchy strictly less than 4/3. For the case of two parallel links our basic mechanism gives 5/4 = 1.25. Then, for the case of two parallel links, we describe an optimal mechanism; its engineered Price of Anarchy lies between 1.191 and 1.192.Comment: 17 pages, 2 figures, preliminary version appeared at ESA 201

Exploring the BWCA (Bino-Wino Co-Annihilation) Scenario for Neutralino Dark Matter

In supersymmetric models with non-universal gaugino masses, it is possible to have opposite-sign SU(2) and U(1) gaugino mass terms. In these models, the gaugino eigenstates experience little mixing so that the lightest SUSY particle remains either pure bino or pure wino. The neutralino relic density can only be brought into accord with the WMAP measured value when bino-wino co-annihilation (BWCA) acts to enhance the dark matter annihilation rate. We map out parameter space regions and mass spectra which are characteristic of the BWCA scenario. Direct and indirect dark matter detection rates are shown to be typically very low. At collider experiments, the BWCA scenario is typified by a small mass gap m_{\tilde Z_2}-m_{\tilde Z_1} ~ 20-80 GeV, so that tree level two body decays of \tilde Z_2 are not allowed. However, in this case the second lightest neutralino has an enhanced loop decay branching fraction to photons. While the photonic neutralino decay signature looks difficult to extract at the Fermilab Tevatron, it should lead to distinctive events at the CERN LHC and at a linear e^+e^- collider.Comment: 44 pages, 21 figure

Indexing Information for Data Forensics

We introduce novel techniques for organizing the indexing structures of how data is stored so that alterations from an original version can be detected and the changed values specifically identified. We give forensic constructions for several fundamental data structures, including arrays, linked lists, binary search trees, skip lists, and hash tables. Some of our constructions are based on a new reduced-randomness construction for nonadaptive combinatorial group testing

Mixed Higgsino Dark Matter from a Reduced SU(3) Gaugino Mass: Consequences for Dark Matter and Collider Searches

In gravity-mediated SUSY breaking models with non-universal gaugino masses, lowering the SU(3) gaugino mass |M_3| leads to a reduction in the squark and gluino masses. Lower third generation squark masses, in turn, diminish the effect of a large top quark Yukawa coupling in the running of the higgs mass parameter m_{H_u}^2, leading to a reduction in the magnitude of the superpotential mu parameter (relative to M_1 and M_2). A low | mu | parameter gives rise to mixed higgsino dark matter (MHDM), which can efficiently annihilate in the early universe to give a dark matter relic density in accord with WMAP measurements. We explore the phenomenology of the low |M_3| scenario, and find for the case of MHDM increased rates for direct and indirect detection of neutralino dark matter relative to the mSUGRA model. The sparticle mass spectrum is characterized by relatively light gluinos, frequently with m(gl)<<m(sq). If scalar masses are large, then gluinos can be very light, with gl->Z_i+g loop decays dominating the gluino branching fraction. Top squarks can be much lighter than sbottom and first/second generation squarks. The presence of low mass higgsino-like charginos and neutralinos is expected at the CERN LHC. The small m(Z2)-m(Z1) mass gap should give rise to a visible opposite-sign/same flavor dilepton mass edge. At a TeV scale linear e^+e^- collider, the region of MHDM will mean that the entire spectrum of charginos and neutralinos are amongst the lightest sparticles, and are most likely to be produced at observable rates, allowing for a complete reconstruction of the gaugino-higgsino sector.Comment: 35 pages, including 26 EPS figure