Balancing Conflict and Cost in the Selection of Negotiation Opponents

Within the context of agent-to-agent purchase negotiations, a problem that has received little attention is that of identifying negotiation opponents in situations where the consequences of conflict and the ability to access resources dynamically vary. Such dynamism poses a number of problems that make it difficult to automate the identification of appropriate opponents. To that end, this paper describes a motivation-based opponent selection mechanism used by a buyer-agent to evaluate and select between an already identified set of seller-agents. Sellers are evaluated in terms of the amount of conflict they are expected to bring to a negotiation and the expected amount of cost a negotiation with them will entail. The mechanism allows trade-offs to be made between conflict and cost minimisation, and experimental results show the effectiveness of the approach

Motivation-based selection of negotiation partners

Negotiation is key to resolving conflicts, allocating resources and establishing cooperation in systems of self interested agents. Often, an agent may have to select between different potential negotiation partners, and identifying which offers the best chance of a successful negotiation is a challenging task. However, poor selection of partners can result in failure or in inefficient outcomes. To that end, this paper describes a motivation-based mechanism to evaluate and select between negotiation candidates. This is achieved by a twofold process: first, acceptable candidates are identified using motivation-based thresholds on objective scoring measures; second, the importance of issues is considered, and expected performance measures are evaluated accordingly. The mechanism is described and empirically evaluated

Can models of agents be transferred between different areas?

One of the main reasons for the sustained activity and interest in the field of agent-based systems, apart from the obvious recognition of its value as a natural and intuitive way of understanding the world, is its reach into very many different and distinct fields of investigation. Indeed, the notions of agents and multi-agent systems are relevant to fields ranging from economics to robotics, in contributing to the foundations of the field, being influenced by ongoing research, and in providing many domains of application. While these various disciplines constitute a rich and diverse environment for agent research, the way in which they may have been linked by it is a much less considered issue. The purpose of this panel was to examine just this concern, in the relationships between different areas that have resulted from agent research. Informed by the experience of the participants in the areas of robotics, social simulation, economics, computer science and artificial intelligence, the discussion was lively and sometimes heated

Reddenings of FGK supergiants and classical Cepheids from spectroscopic data

Accurate and homogeneous atmospheric parameters (Teff, log (g), Vt, [Fe/H]) are derived for 74 FGK non-variable supergiants from high-resolution, high signal-to-noise ratio, echelle spectra. Extremely high precision for the inferred effective temperatures (10-40 K) is achieved by using the line-depth ratio method. The new data are combined with atmospheric values for 164 classical Cepheids, observed at 675 different pulsation phases, taken from our previously published studies. The derived values are correlated with unreddened B-V colours compiled from the literature for the investigated stars in order to obtain an empirical relationship of the form: (B-V)o = 57.984 - 10.3587(log Teff)^2 + 1.67572(log Teff)^3 - 3.356(log (g)) + 0.0321(Vt) + 0.2615[Fe/H] + 0.8833((log (g))(log Teff)). The expression is used to estimate colour excesses E(B-V) for individual supergiants and classical Cepheids, with a precision of +-0.05 mag. for supergiants and Cepheids with n=1-2 spectra, reaching +-0.025 mag. for Cepheids with n>2 spectra, matching uncertainties for the most sophisticated photometric techniques. The reddening scale is also a close match to the system of space reddenings for Cepheids. The application range is for spectral types F0--K0 and luminosity classes I and II.Comment: accepted for publication (MNRAS

Object Segmentation in Images using EEG Signals

This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When an image region, specifically a block of pixels, is displayed we estimate the probability of the block containing the object of interest using a score based on EEG activity. After several such blocks are displayed, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study shows that BCI and simple EEG analysis are useful in locating object boundaries in images.Comment: This is a preprint version prior to submission for peer-review of the paper accepted to the 22nd ACM International Conference on Multimedia (November 3-7, 2014, Orlando, Florida, USA) for the High Risk High Reward session. 10 page

Competition and cooperation:aspects of dynamics in sandpiles

In this article, we review some of our approaches to granular dynamics, now well known to consist of both fast and slow relaxational processes. In the first case, grains typically compete with each other, while in the second, they cooperate. A typical result of {\it cooperation} is the formation of stable bridges, signatures of spatiotemporal inhomogeneities; we review their geometrical characteristics and compare theoretical results with those of independent simulations. {\it Cooperative} excitations due to local density fluctuations are also responsible for relaxation at the angle of repose; the {\it competition} between these fluctuations and external driving forces, can, on the other hand, result in a (rare) collapse of the sandpile to the horizontal. Both these features are present in a theory reviewed here. An arena where the effects of cooperation versus competition are felt most keenly is granular compaction; we review here a random graph model, where three-spin interactions are used to model compaction under tapping. The compaction curve shows distinct regions where 'fast' and 'slow' dynamics apply, separated by what we have called the {\it single-particle relaxation threshold}. In the final section of this paper, we explore the effect of shape -- jagged vs. regular -- on the compaction of packings near their jamming limit. One of our major results is an entropic landscape that, while microscopically rough, manifests {\it Edwards' flatness} at a macroscopic level. Another major result is that of surface intermittency under low-intensity shaking.Comment: 36 pages, 23 figures, minor correction

Recalibration Methodology to Compensate for Changing Fluid Properties in an Individual Nozzle Direct Injection Systems

Limited advancement of direct injection pesticide application systems has been made in recent years, which has hindered further commercialization of this technology. One approach to solving the lag and mixing issues typically associated with injection-based systems is high-pressure individual nozzle injection. However, accurate monitoring of the chemical concentrate flow rate can pose a challenge due to the high pressure, low flow, and changing viscosities of the fluid. A methodology was developed for recalibrating high-pressure chemical concentrate injectors to compensate for fluid property variations and evaluate the performance of this technique for operating injectors in an open-loop configuration. Specific objectives were to (1) develop a method for continuous recalibration of the chemical concentrate injectors to ensure accurate metering of chemicals of varying viscosities and (2) evaluate the recalibration method for estimating individual injector flow rates from a system of multiple injectors to assess potential errors. Test results indicated that the recalibration method was able to compensate for changes in fluid kinematic viscosity (e.g., from temperature changes and/or product variation). Errors were less than 3.4% for the minimum injector duty cycle (DCi) (at 10%) and dropped 0.2% for the maximum DCi (at 90%) for temperature changes of up to 20°C. While larger temperature changes may be expected, these test results showed that the proposed method could be successfully implemented to meet desired injection rates. Because multiple injectors would be used in commercial deployment of this technology, a method was developed to calculate the desired injector flow rate using initial injector calibration factors. Using this multi-injector recalibration method, errors ranged from 0.23% to 0.66% between predicted and actual flow rates for all three injectors