Preface to the special issue on learning approaches for negotiation agents and automated negotiation

2005 ◽  
Vol 21 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Kwang Mong Sim
Keyword(s):  
Automated Negotiation ◽  
Learning Approaches ◽  
Special Issue ◽  
Negotiation Agents

scholarly journals Image Segmentation and Object-Based Image Analysis for Environmental Monitoring: Recent Areas of Interest, Researchers’ Views on the Future Priorities

2020 ◽  
Vol 12 (11) ◽  
pp. 1772
Author(s):  
Brian Alan Johnson ◽  
Lei Ma
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Online Survey ◽  
Accuracy Assessment ◽  
Learning Approaches ◽  
Special Issue ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Wide Range

Image segmentation and geographic object-based image analysis (GEOBIA) were proposed around the turn of the century as a means to analyze high-spatial-resolution remote sensing images. Since then, object-based approaches have been used to analyze a wide range of images for numerous applications. In this Editorial, we present some highlights of image segmentation and GEOBIA research from the last two years (2018–2019), including a Special Issue published in the journal Remote Sensing. As a final contribution of this special issue, we have shared the views of 45 other researchers (corresponding authors of published papers on GEOBIA in 2018–2019) on the current state and future priorities of this field, gathered through an online survey. Most researchers surveyed acknowledged that image segmentation/GEOBIA approaches have achieved a high level of maturity, although the need for more free user-friendly software and tools, further automation, better integration with new machine-learning approaches (including deep learning), and more suitable accuracy assessment methods was frequently pointed out.

scholarly journals Editorial. Design and Cultural Diversity

2019 ◽  
Vol 11 (6) ◽  
Author(s):  
Astrid Skjerven
Keyword(s):  
Cultural Diversity ◽  
Design Education ◽  
Power Transmission ◽  
Innovative Development ◽  
Learning Approaches ◽  
Special Issue

By raising the theme of  Design and Cultural Diversity in this special issue of FormAkademisk we hope to stimulate a broad cross disciplinary discussion on the interplay of cultures within the field of design and design education. The main dimensions of the topic might be summarized as: - The dimensions and meanings of cultural diversity- Politics and power- Transmission and transition of cultures- Heritage and innovation- Indigenous and vernacular traditions versus fashion and euro-centered attitudes- Design and learning approaches These matters are complex, deeply interwoven and interdependent. This series of articles discusses how design might support an innovative development that takes care of diverse traditions and attitudes, supports equality and peaceful co-existence.

Quantitative Concession Behavior Analysis and Prediction for Decision Support in Electronic Negotiations

2014 ◽  
Vol 6 (4) ◽  
pp. 16-30 ◽  
Author(s):  
Réal A. Carbonneau ◽  
Rustam Vahidov ◽  
Gregory E. Kersten
Keyword(s):  
Decision Support ◽  
Quantitative Analysis ◽  
Empirical Evidence ◽  
Real World ◽  
Empirical Data ◽  
Theoretical Basis ◽  
Automated Negotiation ◽  
Electronic Negotiations ◽  
Memory Decay ◽  
Negotiation Agents

Quantitative analysis of negotiation concession behavior is performed based on empirical data with the purpose of providing simple and intuitive decision support in electronic negotiations. Previous work on non-linear concave preferences and subsequent concession crossover provides a theoretical basis for the model. The authors propose a model which quantifies the remaining concession potential for each issue and a generalization of the model which permits the memory/decay of past concessions. These models permit the analysis of negotiators' concession behavior. Using the proposed models, it was possible to quantitatively determine that negotiators in the authors' negotiation case exhibit concession crossover issues and thus have a tendency to give concessions on issues with the most remaining concession potential. This finding provides empirical evidence of concession crossover in actual concessions and the corresponding model permits the design of a simple and intuitive prediction methodology, which could be used in real world negotiations by decision support systems or automated negotiation agents.

scholarly journals Special issue on Machine learning approaches and challenges of missing data in the era of big data

2019 ◽  
Vol 10 (10) ◽  
pp. 2589-2591
Author(s):  
Gwanggil Jeon ◽  
Arun Kumar Sangaiah ◽  
You-Shyang Chen ◽  
Anand Paul
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Missing Data ◽  
Learning Approaches ◽  
Special Issue

scholarly journals Introduction to the special issue on deep learning approaches for machine translation

2017 ◽  
Vol 46 ◽  
pp. 367-373 ◽  
Author(s):  
Marta R. Costa-jussà ◽  
Alexandre Allauzen ◽  
Loïc Barrault ◽  
Kyunghun Cho ◽  
Holger Schwenk
Keyword(s):  
Deep Learning ◽  
Machine Translation ◽  
Learning Approaches ◽  
Special Issue

scholarly journals Artificial Intelligence Techniques for Conflict Resolution

2021 ◽  
Author(s):  
Reyhan Aydoğan ◽  
Tim Baarslag ◽  
Enrico Gerding
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Conflict Resolution ◽  
Computational Models ◽  
Group Decision ◽  
Preference Aggregation ◽  
Automated Negotiation ◽  
Special Issue ◽  
Human Machine Interaction ◽  
Machine Interaction

AbstractConflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new contributions.

Current alternatives on perceptual learning: introduction to special issue on post-cognitivist approaches to perceptual learning

2019 ◽  
Vol 27 (6) ◽  
pp. 355-362 ◽  
Author(s):  
Lorena Lobo
Keyword(s):  
Perceptual Learning ◽  
Cognitive Processes ◽  
Motor Command ◽  
Unified Theory ◽  
Learning Approaches ◽  
Special Issue ◽  
Environmental Aspects ◽  
Alternative Approaches ◽  
The One ◽  
Original Information

This special issue is focused on how perceptual learning is understood from a post-cognitivist approach to cognition. The process of perceptual learning is key in our cognitive life and development: we can learn to discriminate environmental aspects and hence adapt ourselves to it, using our resources intelligently. Perceptual learning, according to the classic cognitivist view, is based on the enrichment of passively received stimuli, a linear operation on sensations that results in a representation of the original information. This representation can be useful for other processes that generate an output, like a motor command, for example. On the contrary, alternative approaches to perceptual learning, different from the one depicted in the classic cognitivist theory, share the ideas that perception and action are intrinsically tied and that cognitive processes rely on embodiment and situatedness. These approaches usually claim that mental representations are not useful concepts, at least when portraying a process of perceptual learning. Approaches within post-cognitivism are not a unified theory, but a diversity of perspectives that need to establish a dialogue among their different methodologies. In particular, this special issue is focused on ecological psychology and enactivism as key traditions within the post-cognitivist constellation.

scholarly journals Machine Learning approaches for convergence of IoT and Blockchain

2020 ◽  
Vol 10 (1) ◽  
pp. 459-460
Author(s):  
Krishna Kant Singh ◽  
B. Balamurugan ◽  
Naveen Chilamkurti Smieee ◽  
Bharat S. Rawal Kshatriya
Keyword(s):  
Machine Learning ◽  
Data Handling ◽  
Learning Approaches ◽  
Special Issue ◽  
Fault Line ◽  
High Quality ◽  
High Quality Research ◽  
Quality Research ◽  
Public Networks ◽  
Iot Devices

AbstractBlockchain plays a significant role in providing security during data handling operations and defines how trusted transactions can be carried out addressing the solution for internet facing vulnerability problems. Blockchain solves the security fault line among AI and IoT, where most of the IoT devices are connected to each other through public networks. This special issue aims to publish a collection of high quality research articles in the area of blockchain, IoT and Machine Learning.

scholarly journals Using Automated Agents to Teach Negotiation

2019 ◽  
Vol 33 ◽  
pp. 9888-9889
Author(s):  
Emmanuel Johnson
Keyword(s):  
Automated Negotiation ◽  
Automated Systems ◽  
Personalized Feedback ◽  
Daily Lives ◽  
Salary Negotiation ◽  
Negotiation Agents ◽  
Future Work

Negotiation is an integral part of our daily lives regardless of occupation. Although ubiquitous to our experience, we are never taught to negotiate. This lack of training presents many consequences from unfair salary negotiation to geopolitical ramification. The ability to resolve conflicts and negotiate is becoming more critical due to the rise of automated systems which look to replace various repetitive task jobs. In hopes of improving human negotiation skills, my work seeks to develop automated negotiation agents capable of providing personalized feedback. In this paper, I provide an overview of my past , current, and future work.

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