Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Rational reasoning or adaptive behavior? Evidence from two-person beauty contest games

Many experiments have shown that human subjects do not necessarily behave in line with game theoretic assumptions and solution concepts. The reasons for this non-conformity are multiple. In this paper we study the argument whether a deviation from game theory is because subjects are rational, but doubt that others are rational as well, compared to the argument that subjects, in general, are boundedly rational themselves. To distinguish these two hypotheses, we study behavior in repeated 2-person and many-person Beauty-Contest-Games which are strategically different from one another. We analyze four different treatments and observe that convergence toward equilibrium is driven by learning through the information about the other player s choice and adaptation rather than self-initiated rational reasoning.

Adaptive model selection using empirical complexities

Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

Adaptive dynamics and the implementation problem with complete information

This paper studies the equilibrating process of several implementationmechanisms using naive adaptive dynamics. We show that the dynamics convergeand are stable, for the canonical mechanism of implementation in Nash equilibrium.In this way we cast some doubt on the criticism of ``complexity'' commonlyused against this mechanism. For mechanisms that use more refined equilibrium concepts,the dynamics converge but are not stable. Some papers in the literatureon implementation with refined equilibrium concepts have claimed that themechanisms they propose are ``simple'' and implement ``everything'' (incontrast with the canonical mechanism). The fact that some of these ``simple''mechanisms have unstable equilibria suggests that these statements shouldbe interpreted with some caution.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Genetic variants of the FADS gene cluster and ELOVL gene family, colostrums LC-PUFA levels, breastfeeding, and child cognition

Introduction: Breastfeeding effects on cognition are attributed to long-chain polyunsaturated fatty acids (LC-PUFAs), but controversy persists. Genetic variation in fatty acid desaturase (FADS) and elongase (ELOVL) enzymes has been overlooked when studying the effects of LC-PUFAs supply on cognition. We aimed to: 1) to determine whether maternal genetic variants in the FADS cluster and ELOVL genes contribute to differences in LC-PUFA levels in colostrum; 2) to analyze whether these maternal variants are related to child cognition; and 3) to assess whether children's variants modify breastfeeding effects on cognition. Methods: Data come from two population-based birth cohorts (n = 400 mother-child pairs from INMA-Sabadell; and n = 340 children from INMA-Menorca). LC-PUFAs were measured in 270 colostrum samples from INMA-Sabadell. Tag SNPs were genotyped both in mothers and children (13 in the FADS cluster, 6 in ELOVL2, and 7 in ELOVL5). Child cognition was assessed at 14 mo and 4 y using the Bayley Scales of Infant Development and the McCarthy Scales of Children"s Abilities, respectively. Results: Children of mothers carrying genetic variants associated with lower FADS1 activity (regulating AA and EPA synthesis), higher FADS2 activity (regulating DHA synthesis), and with higher EPA/AA and DHA/AA ratios in colostrum showed a significant advantage in cognition at 14 mo (3.5 to 5.3 points). Not being breastfed conferred an 8- to 9-point disadvantage in cognition among children GG homozygote for rs174468 (low FADS1 activity) but not among those with the A allele. Moreover, not being breastfed resulted in a disadvantage in cognition (5 to 8 points) among children CC homozygote for rs2397142 (low ELOVL5 activity), but not among those carrying the G allele. Conclusion: Genetically determined maternal supplies of LC-PUFAs during pregnancy and lactation appear to be crucial for child cognition. Breastfeeding effects on cognition are modified by child genetic variation in fatty acid desaturase and elongase enzymes.

Viticulture under climate change : understanding vulnerability and adaptive capacity of wineries and growers. A case study in El Penedès region, Catalonia

Climate change may pose challenges and opportunities to viticulture, and much research has focused in studying the likely impacts on grapes and wine production in different regions worldwide. This study assesses the vulnerability and adaptive capacity of the viticulture sector under changing climate conditions, based on a case study in El Penedès region, Catalonia. Farm assets, livelihood strategies, farmer-market interactions and climate changes perceptions are analysed through semi-structured interviews with different types of wineries and growers. Both types of actors are equally exposed to biophysical stressors but unevenly affected by socioeconomic changes. While wineries are vulnerable because of the current economic crisis and the lack of diversification of their work, which may affect their income or production, growers are mainly affected by the low prices of their products and the lack of fix contracts. These socioeconomic stressors strongly condition their capacity to adapt to climate change, meaning that growers prioritize their immediate income problems, rather than future socioeconomic or climate threats. Therefore, growers undertake reactive adaptation to climate changing conditions, mainly based on ancient knowledge, whilst wineries combine both reactive and anticipatory adaptation practices. These circumstances should be addressed in order to allow better anticipatory adaptation to be implemented, thus avoiding future climate threats.

The underestimation of compliance to direct help requests explained by adaptive sampling

Helping behavior is any intentional behavior that benefits another living being or group (Hogg & Vaughan, 2010). People tend to underestimate the probability that others will comply with their direct requests for help (Flynn & Lake, 2008). This implies that when they need help, they will assess the probability of getting it (De Paulo, 1982, cited in Flynn & Lake, 2008) and then they will tend to estimate one that is actually lower than the real chance, so they may not even consider worth asking for it. Existing explanations for this phenomenon attribute it to a mistaken cost computation by the help seeker, who will emphasize the instrumental cost of “saying yes”, ignoring that the potential helper also needs to take into account the social cost of saying “no”. And the truth is that, especially in face-to-face interactions, the discomfort caused by refusing to help can be very high. In short, help seekers tend to fail to realize that it might be more costly to refuse to comply with a help request rather than accepting. A similar effect has been observed when estimating trustworthiness of people. Fetchenhauer and Dunning (2010) showed that people also tend to underestimate it. This bias is reduced when, instead of asymmetric feedback (getting feedback only when deciding to trust the other person), symmetric feedback (always given) was provided. This cause could as well be applicable to help seeking as people only receive feedback when they actually make their request but not otherwise. Fazio, Shook, and Eiser (2004) studied something that could be reinforcing these outcomes: Learning asymmetries. By means of a computer game called BeanFest, they showed that people learn better about negatively valenced objects (beans in this case) than about positively valenced ones. This learning asymmetry esteemed from “information gain being contingent on approach behavior” (p. 293), which could be identified with what Fetchenhauer and Dunning mention as ‘asymmetric feedback’, and hence also with help requests. Fazio et al. also found a generalization asymmetry in favor of negative attitudes versus positive ones. They attributed it to a negativity bias that “weights resemblance to a known negative more heavily than resemblance to a positive” (p. 300). Applied to help seeking scenarios, this would mean that when facing an unknown situation, people would tend to generalize and infer that is more likely that they get a negative rather than a positive outcome from it, so, along with what it was said before, people will be more inclined to think that they will get a “no” when requesting help. Denrell and Le Mens (2011) present a different perspective when trying to explain judgment biases in general. They deviate from the classical inappropriate information processing (depicted among other by Fiske & Taylor, 2007, and Tversky & Kahneman, 1974) and explain this in terms of ‘adaptive sampling’. Adaptive sampling is a sampling mechanism in which the selection of sample items is conditioned by the values of the variable of interest previously observed (Thompson, 2011). Sampling adaptively allows individuals to safeguard themselves from experiences they went through once and turned out to lay negative outcomes. However, it also prevents them from giving a second chance to those experiences to get an updated outcome that could maybe turn into a positive one, a more positive one, or just one that regresses to the mean, whatever direction that implies. That, as Denrell and Le Mens (2011) explained, makes sense: If you go to a restaurant, and you did not like the food, you do not choose that restaurant again. This is what we think could be happening when asking for help: When we get a “no”, we stop asking. And here, we want to provide a complementary explanation for the underestimation of the probability that others comply with our direct help requests based on adaptive sampling. First, we will develop and explain a model that represents the theory. Later on, we will test it empirically by means of experiments, and will elaborate on the analysis of its results.

Efficacy and safety of aripiprazole in the treatment of bipolar disorder: a systematic review.

Abstract BACKGROUND: The current article is a systematic review concerning the efficacy and safety of aripiprazole in the treatment of bipolar disorder. METHODS: A systematic Medline and repositories search concerning the usefulness of aripiprazole in bipolar disorder was performed, with the combination of the words 'aripiprazole' and 'bipolar'. RESULTS: The search returned 184 articles and was last updated on 15 April 2009. An additional search included repositories of clinical trials and previous systematic reviews specifically in order to trace unpublished trials. There were seven placebo-controlled randomised controlled trials (RCTs), six with comparator studies and one with add-on studies. They assessed the usefulness of aripiprazole in acute mania, acute bipolar depression and during the maintenance phase in comparison to placebo, lithium or haloperidol. CONCLUSION: Aripiprazole appears effective for the treatment and prophylaxis against mania. The data on bipolar depression are so far negative, however there is a need for further study at lower dosages. The most frequent adverse effects are extrapyramidal signs and symptoms, especially akathisia, without any significant weight gain, hyperprolactinaemia or laboratory test changes.

Efficacy of a dilemma-focused intervention for unipolar depression: study protocol for a multicenter randomized controlled trial

Background Depression is one of the more severe and serious health problems because of its morbidity, disabling effects and for its societal and economic burden. Despite the variety of existing pharmacological and psychological treatments, most of the cases evolve with only partial remission, relapse and recurrence. Cognitive models have contributed significantly to the understanding of unipolar depression and its psychological treatment. However, success is only partial and many authors affirm the need to improve those models and also the treatment programs derived from them. One of the issues that requires further elaboration is the difficulty these patients experience in responding to treatment and in maintaining therapeutic gains across time without relapse or recurrence. Our research group has been working on the notion of cognitive conflict viewed as personal dilemmas according to personal construct theory. We use a novel method for identifying those conflicts using the repertory grid technique (RGT). Preliminary results with depressive patients show that about 90% of them have one or more of those conflicts. This fact might explain the blockage and the difficult progress of these patients, especially the more severe and/or chronic. These results justify the need for specific interventions focused on the resolution of these internal conflicts. This study aims to empirically test the hypothesis that an intervention focused on the dilemma(s) specifically detected for each patient will enhance the efficacy of cognitive behavioral therapy (CBT) for depression. Design A therapy manual for a dilemma-focused intervention will be tested using a randomized clinical trial by comparing the outcome of two treatment conditions: combined group CBT (eight, 2-hour weekly sessions) plus individual dilemma-focused therapy (eight, 1-hour weekly sessions) and CBT alone (eight, 2-hour group weekly sessions plus eight, 1-hour individual weekly sessions). Method Participants are patients aged over 18 years meeting diagnostic criteria for major depressive disorder or dysthymic disorder, with a score of 19 or above on the Beck depression inventory, second edition (BDI-II) and presenting at least one cognitive conflict (implicative dilemma or dilemmatic construct) as assessed using the RGT. The BDI-II is the primary outcome measure, collected at baseline, at the end of therapy, and at 3- and 12-month follow-up; other secondary measures are also used. Discussion We expect that adding a dilemma-focused intervention to CBT will increase the efficacy of one of the more prestigious therapies for depression, thus resulting in a significant contribution to the psychological treatment of depression. Trial registration ISRCTN92443999; ClinicalTrials.gov Identifier: NCT01542957.

An Adaptive Remeshing Procedure for Proximity Maneuvering Spacecraft Formations

We consider a methodology to optimally obtain reconfigurations of spacecraft formations. It is based on the discretization of the time interval in subintervals (called the mesh) and the obtainment of local solutions on them as a result of a variational method. Applied to a libration point orbit scenario, in this work we focus on how to find optimal meshes using an adaptive remeshing procedure and on the determination of the parameter that governs it

Efficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis.

Randomized, controlled trials have demonstrated efficacy for second-generation antipsychotics in the treatment of acute mania in bipolar disorder. Despite depression being considered the hallmark of bipolar disorder, there are no published systematic reviews or meta-analyses to evaluate the efficacy of modern atypical antipsychotics in bipolar depression. We systematically reviewed published or registered randomized, double-blind, placebo-controlled trials (RCTs) of modern antipsychotics in adult bipolar I and/or II depressive patients (DSM-IV criteria). Efficacy outcomes were assessed based on changes in the Montgomery-Asberg Depression Rating Scale (MADRS) during an 8-wk period. Data were combined through meta-analysis using risk ratio as an effect size with a 95% confidence interval (95% CI) and with a level of statistical significance of 5% (p<0.05). We identified five RCTs; four involved antipsychotic monotherapy and one addressed both monotherapy and combination with an antidepressant. The two quetiapine trials analysed the safety and efficacy of two doses: 300 and 600 mg/d. The only olanzapine trial assessed olanzapine monotherapy within a range of 5-20 mg/d and olanzapine-fluoxetine combination within a range of 5-20 mg/d and 6-12 mg/d, respectively. The two aripiprazole placebo-controlled trials assessed doses of 5-30 mg/d. Quetiapine and olanzapine trials (3/5, 60%) demonstrated superiority over placebo (p<0.001). Only 2/5 (40%) (both aripiprazole trials) failed in the primary efficacy measure after the first 6 wk. Some modern antipsychotics (quetiapine and olanzapine) have demonstrated efficacy in bipolar depressive patients from week 1 onwards. Rapid onset of action seems to be a common feature of atypical antipsychotics in bipolar depression. Comment in The following popper user interface control may not be accessible. Tab to the next button to revert the control to an accessible version.Destroy user interface controlEfficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis--results to be interpreted with caution.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.