1,609 research outputs found
is the author of many papers and reports. Tim was born in 1950.
No full textTim Pearce has responsibility for work relating to vehicle safety and institutional strengthening in developing countries. He was involved in UK transport-related research projects for 15 years before specialising in problems relating to developing countries. During the last 10 years he has been closely involved in the problems of the roadworthiness of vehicles both from the technical and institutional sides. He has worke
What to bid and when to stop
No full textNegotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a large interest in the automation of negotiation, for example in the setting of e-commerce. This interest is fueled by the promise of automated agents eventually being able to negotiate on behalf of human negotiators.Every year, automated negotiation agents are improving in various ways, and there is now a large body of negotiation strategies available, all with their unique strengths and weaknesses. For example, some agents are able to predict the opponent's preferences very well, while others focus more on having a sophisticated bidding strategy. The problem however, is that there is little incremental improvement in agent design, as the agents are tested in varying negotiation settings, using a diverse set of performance measures. This makes it very difficult to meaningfully compare the agents, let alone their underlying techniques. As a result, we lack a reliable way to pinpoint the most effective components in a negotiating agent.There are two major advantages of distinguishing between the different components of a negotiating agent's strategy: first, it allows the study of the behavior and performance of the components in isolation. For example, it becomes possible to compare the preference learning component of all agents, and to identify the best among them. Second, we can proceed to mix and match different components to create new negotiation strategies., e.g.: replacing the preference learning technique of an agent and then examining whether this makes a difference. Such a procedure enables us to combine the individual components to systematically explore the space of possible negotiation strategies.To develop a compositional approach to evaluate and combine the components, we identify structure in most agent designs by introducing the BOA architecture, in which we can develop and integrate the different components of a negotiating agent. We identify three main components of a general negotiation strategy; namely a bidding strategy (B), possibly an opponent model (O), and an acceptance strategy (A). The bidding strategy considers what concessions it deems appropriate given its own preferences, and takes the opponent into account by using an opponent model. The acceptance strategy decides whether offers proposed by the opponent should be accepted.The BOA architecture is integrated into a generic negotiation environment called Genius, which is a software environment for designing and evaluating negotiation strategies. To explore the negotiation strategy space of the negotiation research community, we amend the Genius repository with various existing agents and scenarios from literature. Additionally, we organize a yearly international negotiation competition (ANAC) to harvest even more strategies and scenarios. ANAC also acts as an evaluation tool for negotiation strategies, and encourages the design of negotiation strategies and scenarios.We re-implement agents from literature and ANAC and decouple them to fit into the BOA architecture without introducing any changes in their behavior. For each of the three components, we manage to find and analyze the best ones for specific cases, as described below. We show that the BOA framework leads to significant improvements in agent design by wining ANAC 2013, which had 19 participating teams from 8 international institutions, with an agent that is designed using the BOA framework and is informed by a preliminary analysis of the different components.In every negotiation, one of the negotiating parties must accept an offer to reach an agreement. Therefore, it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When contemplating whether to accept an offer, the agent is faced with the acceptance dilemma: accepting the offer may be suboptimal, as better offers may still be presented before time runs out. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. We classify and compare state-of-the-art generic acceptance conditions. We propose new acceptance strategies and we demonstrate that they outperform the other conditions. We also provide insight into why some conditions work better than others and investigate correlations between the properties of the negotiation scenario and the efficacy of acceptance conditions.Later, we adopt a more principled approach by applying optimal stopping theory to calculate the optimal decision on the acceptance of an offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We show that the proposed approach is able to find the optimal time to accept, and improves upon all existing acceptance strategies.Another principal component of a negotiating agent's strategy is its ability to take the opponent's preferences into account. The quality of an opponent model can be measured in two different ways. One is to use the agent's performance as a benchmark for the model's quality. We evaluate and compare the performance of a selection of state-of-the-art opponent modeling techniques in negotiation. We provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. We identify a class of simple and surprisingly effective opponent modeling techniques that did not receive much previous attention in literature.The other way to measure the quality of an opponent model is to directly evaluate its accuracy by using similarity measures. We review all methods to measure the accuracy of an opponent model and we then analyze how changes in accuracy translate into performance differences. Moreover, we pinpoint the best predictors for good performance. This leads to new insights concerning how to construct an opponent model, and what we need to measure when optimizing performance.Finally, we take two different approaches to gain more insight into effective bidding strategies. We present a new classification method for negotiation strategies, based on their pattern of concession making against different kinds of opponents. We apply this technique to classify some well-known negotiating strategies, and we formulate guidelines on how agents should bid in order to be successful, which gives insight into the bidding strategy space of negotiating agents. Furthermore, we apply optimal stopping theory again, this time to find the concessions that maximize utility for the bidder against particular opponents. We show there is an interesting connection between optimal bidding and optimal acceptance strategies, in the sense that they are mirrored versions of each other.Lastly, after analyzing all components separately, we put the pieces back together again. We take all BOA components accumulated so far, including the best ones, and combine them all together to explore the space of negotiation strategies.We compute the contribution of each component to the overall negotiation result, and we study the interaction between components. We find that combining the best agent components indeed makes the strongest agents. This shows that the component-based view of the BOA architecture not only provides a useful basis for developing negotiating agents but also provides a useful analytical tool. By varying the BOA components we are able to demonstrate the contribution of each component to the negotiation result, and thus analyze the significance of each. The bidding strategy is by far the most important to consider, followed by the acceptance conditions and finally followed by the opponent model.Our results validate the analytical approach of the BOA framework to first optimize the individual components, and then to recombine them into a negotiating agent
Accepting Optimally in Automated Negotiation with Incomplete Information (abstract)
No full textIntelligent SystemsElectrical Engineering, Mathematics and Computer Scienc
Long-lived discs in T associations: Pre-main-sequence ages for low-mass stars
No full textIn this thesis, ages have been derived for 4 young clusters by fitting the pre-main-sequence stars with semi-empirical models in colour-magnitude diagrams. Combining these ages with the (consistent) set presented in previous work, the first robust evidence of increased circumstellar disc lifetimes in low-mass, low-density regions is obtained. To obtain this result, the following steps were necessary:
• Semi-empirical model isochrones have been constructed in a number of rizJHK photometric systems. These models overcome the issues typically seen in purely theoretical models in which the blue flux of low-mass stars is overestimated. These models are presented in a number of widely used filter sets for the first time, allowing for wider use with new clusters. Additionally the models constructed in previous filter sets have been refined using new observations.
• To support the construction of these models, upper-main-sequence fitting is performed for 2 fiducial clusters, and it is demonstrated that the resulting age and distance measurements are consistent with other measures.
• A new reduction process for data in the Blanco-DECam system is presented, and it is shown that the DECam photometric system is well characterised.
• A photometric method for dereddening stars individually in regions of spatially variable extinction is presented, and applied to the young regions in this study. This method of photometric dereddening can be applied to large numbers of stars, greatly decreasing the time investment needed compared to spectroscopic methods.
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The ages derived for the young clusters using the semi-empirical models are around a factor 2 older than typically assumed in the literature, which is in-line with that seen for the ages derived for other clusters using the same technique. By considering the disc fraction in these clusters as a function of age, it is shown that Taurus and Chamaeleon show a significant excess of discs compared to a set of massive, dense clusters of similar age. This is clear evidence that discs seem to survive longer in this low-mass, low-density region, giving crucial hints at different disc evolution in these regions. ρ-Oph is a low-mass region with a high stellar density, and so could be used to identify the dominant mechanism leading to these long-lived discs. However the presence of a similar disc excess in ρ-Oph is dependent on the assumed distance, which is currently poorly constrained, and so the dominant mechanism is still unclear
Exploring the strategy space of negotiating agents: a framework for bidding, learning and accepting in automated negotiation
No full textThis book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures
T-Cell Subsets Predict Mortality in Malnourished Zambian Adults Initiating Antiretroviral Therapy.
No full textThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedTo estimate the prognostic value of T-cell subsets in Zambian patients initiating antiretroviral therapy (ART), and to assess the impact of a nutritional intervention on T-cell subsets.This work was supported by European and Developing Countries Clinical Trials Partnership grant # IP.2009.33011.004; trial foods were prepared and supplied by Nutriset, Malauney, Franc
A polymorphism of the TIM-1 IgV domain: Implications for the susceptibility to filovirus infection
No full textFiloviruses, including Ebola and Marburg viruses, cause severe hemorrhagic fever in humans and nonhuman primates with mortality rates of up to 90%. Human T-cell immunoglobulin and mucin domain 1 (TIM-I) is one of the host proteins that have been shown to promote filovirus entry into cells. In this study, we cloned TIM-1 genes from three different African green monkey kidney cell lines (Vero E6, COS-I, and BSC-1) and found that TIM-1 of Vero E6 had a 23-amino acid deletion and 6 amino acid substitutions compared with those of COS-1 and BSC-1. Interestingly, Vero E6 TIM-I had a greater ability to promote the infectivity of vesicular stomatitis viruses pseudotyped with filovirus glycoproteins than COS-1-derived TIM-I. We further found that the increased ability of Vero E6 TIM-1 to promote virus infectivity was most likely due to a single amino acid difference between these TIM-1s. These results suggest that a polymorphism of the TIM-I molecules is one of the factors that influence cell susceptibility to filovirus infection, providing a new insight into the molecular basis for the filovirus host range. (C) 2014 Elsevier Inc. All rights reserved
Acceptance conditions in automated negotiation
No full textIn every negotiation with a deadline, one of the negotiating parties has to accept an offer to avoid a break off. A break off is usually an undesirable outcome for both parties, therefore it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When designing such conditions one is faced with the acceptance dilemma: accepting the current offer may be suboptimal, as better offers may still be presented. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. Motivated by the challenges of bilateral negotiations between automated agents and by the results and insights of the automated negotiating agents competition (ANAC), we classify and compare state-of-the-art generic acceptance conditions. We focus on decoupled acceptance conditions, i.e. conditions that do not depend on the bidding strategy that is used. We performed extensive experiments to compare the performance of acceptance conditions in combination with a broad range of bidding strategies and negotiation domains. Furthermore we propose new acceptance conditions and we demonstrate that they outperform the other conditions that we study. In particular, it is shown that they outperform the standard acceptance condition of comparing the current offer with the offer the agent is ready to send out. We also provide insight in to why some conditions work better than others and investigate correlations between the properties of the negotiation environment and the efficacy of acceptance conditions.MediamaticsElectrical Engineering, Mathematics and Computer Scienc
Nostalgia: content, triggers, functions
No full textSeven methodologically diverse studies addressed 3 fundamental questions about nostalgia. Studies 1 and 2 examined the content of nostalgic experiences. Descriptions of nostalgic experiences typically featured the self as a protagonist in interactions with close others (e.g., friends) or in momentous events (e.g., weddings). Also, the descriptions contained more expressions of positive than negative affect and often depicted the redemption of negative life scenes by subsequent triumphs. Studies 3 and 4 examined triggers of nostalgia and revealed that nostalgia occurs in response to negative mood and the discrete affective state of loneliness. Studies 5, 6, and 7 investigated the functional utility of nostalgia and established that nostalgia bolsters social bonds, increases positive self-regard, and generates positive affect. These findings demarcate key landmarks in the hitherto uncharted research domain of nostalgi
Transiting exoplanets: characterisation in the presence of stellar activity
No full textThe combined observations of a planet’s transits and the radial velocity variations of its host star allow the determination of the planet’s orbital parameters, and most inter- estingly of its radius and mass, and hence its mean density. Observed densities provide important constraints to planet structure and evolution models. The uncertainties on the parameters of large exoplanets mainly arise from those on stellar masses and radii. For small exoplanets, the treatment of stellar variability limits the accuracy on the de- rived parameters. The goal of this PhD thesis was to reduce these sources of uncertainty by developing new techniques for stellar variability filtering and for the determination of stellar temperatures, and by robustly fitting the transits taking into account external constraints on the planet’s host star.
To this end, I developed the Iterative Reconstruction Filter (IRF), a new post-detection stellar variability filter. By exploiting the prior knowledge of the planet’s orbital period, it simultaneously estimates the transit signal and the stellar variability signal, using a com- bination of moving average and median filters. The IRF was tested on simulated CoRoT light curves, where it significantly improved the estimate of the transit signal, particu- lary in the case of light curves with strong stellar variability. It was then applied to the light curves of the first seven planets discovered by CoRoT, a space mission designed to search for planetary transits, to obtain refined estimates of their parameters. As the IRF preserves all signal at the planet’s orbital period, t can also be used to search for secondary eclipses and orbital phase variations for the most promising cases. This en- abled the detection of the secondary eclipses of CoRoT-1b and CoRoT-2b in the white (300–1000 nm) CoRoT bandpass, as well as a marginal detection of CoRoT-1b’s orbital phase variations. The wide optical bandpass of CoRoT limits the distinction between thermal emission and reflected light contributions to the secondary eclipse.
I developed a method to derive precise stellar relative temperatures using equiv- alent width ratios and applied it to the host stars of the first eight CoRoT planets. For stars with temperature within the calibrated range, the derived temperatures are con- sistent with the literature, but have smaller formal uncertainties. I then used a Markov Chain Monte Carlo technique to explore the correlations between planet parameters derived from transits, and the impact of external constraints (e.g. the spectroscopically derived stellar temperature, which is linked to the stellar density).
Globally, this PhD thesis highlights, and in part addresses, the complexity of perform- ing detailed characterisation of transit light curves. Many low amplitude effects must be taken into account: residual stellar activity and systematics, stellar limb darkening, and the interplay of all available constraints on transit fitting. Several promising areas for further improvements and applications were identified. Current and future high precision photometry missions will discover increasing numbers of small planets around relatively active stars, and the IRF is expected to be useful in characterising them.School of Physics, University of Exete
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