Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019

The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 posed five negotiation challenges: automated negotiation with partial preferences, repeated human-agent negotiation, negotiation in supply-chain management, negotiating in the strategic game of Diplomacy, and in the Werewolf game. This paper introduces the challenges and discusses the main findings and lessons learnt per league

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

The study of the factors affecting stadium attendance by Yankees' fans

The purpose of this study was to investigate factors affecting Yankees' fans' attendance. The study population was randomly selected (n = 707) and included supporters of the Yankees' Baseball Team participating at the Yankee Stadium in the 2017 seasons of American Major League Baseball. Materials and Methods: The Stadium Attendance and Non-Attendance Reason Scale (SANARS) created by Soyguden in 2013 contained 30 questions to determine reasons affecting Yan-kees' fans' attendance. The reasons affecting (SANARS) scale was used. Descriptive statistics, inde-pendent sample t-tests, factor analysis, and a one-way ANOVA were the statistical methods used to analyze the data. Results: In general, stadium attendance of the supporters was affected by the following factors: Personal Relaxation Opportunities, Team Effect, and General Atmosphere. In con-trast to affecting attendance, the following factors were found to affect nonattendance of Yankees' fans: Negative Environmental Conditions and Negative Ergonomic Conditions. Of all factors affect-ing supporters' attendance to the stadiums, "Personal Relaxation Opportunities" was the most in-fluential. Conclusions: The addition of more fan-based recreational activities in stadiums on game -day is recommended. The factor in this study found to influence stadium attendance / non-attend-ance the most was "Negative Environmental Conditions." Thus, there is a need to improve negative environmental conditions

Hearing loss in behçet's disease

PubMedID: 8534025In order to determine the characteristics and incidence of hearing loss in Behçet's disease, 72 consecutive cases and 72 sex- and age-matched normal subjects were submitted to this study. Detailed audiologic tests were performed in all cases. Twenty patients (27%) showed some degree of hearing loss; but in only 7 patients (9%) was the average of the frequencies between 500 to 4,000 Hz more than 25 dB hearing level, and the cochlear function of 43 patients (59%) was within the 25-dB range in all frequencies. The averaged pure tone audiograms of the two groups showed a statistically significant hearing loss in the Behçet's group. No relationship could be found between hearing loss and other system involvements. There was no correlation between hearing loss and duration of the disease, but the mean age of the Behçet's patients with hearing loss was found to be significantly higher than the mean age of the patients without hearing loss. © 1995, SAGE Publications. All rights reserved

How microplastics quantities increase with flood events? An example from Mersin Bay NE Levantine coast of Turkey

PubMedID: 29674212Floods caused by heavy rain carry significant amounts of pollutants into marine environments. This study evaluates the effect of multiple floods that occurred in the northeastern Mediterranean region in Turkey between December 2016 and January 2017 on the microplastic pollution in the Mersin Bay. Sampling was repeated in four different stations both before and after the flood period, and it was determined that in the four stations, there was an average of 539,189 MPs/km2 before the flood, and 7,699,716 MPs/km2 afterwards, representing a 14-fold increase. Fourteen different polymer types were detected in an ATR FT-IR analysis, eight of which were not found in samples collected before the floods. The most common polymer type was identified as polyethylene both pre- and post-flood. The mean particle size, which was 2.37 mm in the pre-flood period, decreased to 1.13 mm in the post-flood period. A hydrodynamic modeling study was implemented to hindcast the current structure and the spatial and temporal distributions of microplastics within the study area. In conclusion, heavy rain and severe floods can dramatically increase the microplastic levels in the sea. © 2018 Elsevier Lt

The fifth automated negotiating agents competition (ANAC 2014)

Due to copyright restrictions, the access to the full text of this article is only available via subscription.In May 2014, we organized the Fifth International Automated Negotiating Agents Competition (ANAC 2014) in conjunction with AAMAS 2014. ANAC is an international competition that challenges researchers to develop a successful automated negotiator for scenarios where there is incomplete information about the opponent. One of the goals of this competition is to help steer the research in the area of bilateral multi-issue negotiations, and to encourage the design of generic negotiating agents that are able to operate in a variety of scenarios. 21 teams from 13 different institutes competed in ANAC 2014. This chapter describes the participating agents and the setup of the tournament, including the different negotiation scenarios that were used in the competition. We report on the results of the qualifying and final round of the tournament

A machine learning approach for mechanism selection in complex negotiations

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the characteristics of the underlying negotiation problem (e.g. on the complexity of participant’s utility functions, as well as the degree of conflict between participants). While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by (1) defining a set of scenario metrics to capture the relevant features of negotiation problems, (2) evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, (3) applying machine learning techniques to identify which mechanisms work best with which scenarios, and (4) demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.ITEA M2MGrids Project ; Spanish Ministry of Economy and Competitivenes

Alternating offers protocols for multilateral negotiation

This paper presents a general framework for multilateral turn-taking protocols and two fully specified protocols namely Stacked Alternating Offers Protocol (SAOP) and Alternating Multiple Offers Protocol (AMOP). In SAOP, agents can make a bid, accept the most recent bid or walk way (i.e., end the negotiation without an agreement) when it is their turn. AMOP has two different phases: bidding and voting. The agents make their bid in the bidding phase and vote the underlying bids in the voting phase. Unlike SAOP, AMOP does not support walking away option. In both protocols, negotiation ends when the negotiating agents reach a joint agreement or some deadline criterion applies. The protocols have been evaluated empirically, showing that SAOP outperforms AMOP with the same type of conceder agents in a time-based deadline setting. SAOP was used in the ANAC 2015 competition for automated negotiating agents.ITE