Building capacity in climate change policy analysis and negotiation: methods and technologies

Capacity building is often cited as the reason “we cannot just pour money into developing countries” and why so many development projects fail because their design does not address local conditions. It is therefore a key technical and political concept in international development. Some of the poorest countries in the world are also some of the most vulnerable to the impacts of climate change. Their vulnerability is in part due to a lack of capacity to plan and anticipate the effects of climate change on crops, water resources, urban electricity demand etc. What capacities do these countries lack to deal with climate change? How will they cope? What steps can they take to reduce their vulnerability? This innovative and high-profile research project was part of a larger project (called C3D) and conducted with non-governmental organisations in Senegal, South Africa and Sri Lanka. The research involved several participatory workshops and a questionnaire to all three research centres

Computational model of negotiation skills in virtual artificial agents

Negotiation skills represent crucial abilities for engaging in effective social interactions in formal and informal settings. Serious games, intelligent systems and virtual agents can provide solid tools upon which one-to-one training and assessment can be reliably made available. The aim of the present work is to fill the gap between the recent growing interest towards soft skills, and the lack of a robust and modern methodology for supporting their investigation. A computational model for the development of Enact, a 3D virtual intelligent platform for training and testing negotiation skills, will be presented. The serious game allows users to interact with simulated peers in scenarios depicting daily life situations and receive a psychological assessment and adaptive training reflecting their negotiation abilities. To pursue this goal, this work has gone through different research stages, each with a unique methodology, results and discussion described in its specific section. In the first phase, the platform was designed to operationalize the examined negotiation theory, developed and assessed. The negotiation styles considered, consistently with previous findings, have been found not to correlate with personality traits, coping strategies and perceived self-efficacy. The serious game has been widely tested for its usability and underwent two development and release stages aimed at improving its accuracy, usability and likeability. The variables measured by the platform have been found to predict in all cases at least two of the negotiation styles considered. Concerning the user feedback, the game has been judged as useful, more pleasant than the traditional test, and the perceived time spent on the game resulted significantly lower than the real time spent. In the second stage of this research, the game scenarios were used to collect a dataset of documents containing natural language negotiations between users and the virtual agents. The dataset was used to assess the correlations between the personal pronouns' use and the negotiation styles. Results showed that more engaged styles generally used pronouns with a significantly higher frequency than less engaged styles. Styles with a high concern for self showed a higher frequency of singular personal pronouns while styles with a high concern for others used significantly more relational pronouns. The corpus of documents was also used to perform multiclass classification on the negotiation styles using machine learning. Both linear (SVM) and non-linear models (MNB, CNN) performed reliably with a state-of-the-art accuracy

Online dispute resolution: an artificial intelligence perspective

Litigation in court is still the main dispute resolution mode. However, given the amount and characteristics of the new disputes, mostly arising out of electronic contracting, courts are becoming slower and outdated. Online Dispute Resolution (ODR) recently emerged as a set of tools and techniques, supported by technology, aimed at facilitating conflict resolution. In this paper we present a critical evaluation on the use of Artificial Intelligence (AI) based techniques in ODR. In order to fulfill this goal, we analyze a set of commercial providers (in this case twenty four) and some research projects (in this circumstance six). Supported by the results so far achieved, a new approach to deal with the problem of ODR is proposed, in which we take on some of the problems identified in the current state of the art in linking ODR and AI.The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009).Acknowledgments. The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009)

A Step towards Softbots: Easy2Shop, a Multi Agent based Shopping bot

With the emergence and omnipresence of e-commerce on the internet, online purchasing assistants and applications have made their appearance. More commonly known as “shop bots†these intelligent agents facilitate the purchasing process, therefore saving time and money. Most shop bots provide you with a list of companies offering the best price and service for the product that you want. The first shop bot Bargain Finder was developed in 1995 by Andersen consulting and it was designed to help people find only musical CDs. Today, Shop bots are capable of finding a wide variety of products and services offered on the internet. These intelligent agents help you to make the best choice when looking for CDs, DVDs, books, computers, software, and cars. Keywords: Intelligent agents, Shopping bots, E-Commerce, Multi agents, Robotics, Easy2Shop, Intelligent agent criteria, Soft bots

Students as change agents: new ways of engaging with learning and teaching in higher education

This is a set of practitioner resources for those wanting to set up student-based research projects in their institutions

Supporting the tutor in the design and support of adaptive e-learning

The further development and deployment of e-learning faces a number of threats. First, in order to meet the increasing demands of learners, staff have to develop and plan a wide and complex variety of learning activities that, in line with contemporary pedagogical models, adapt to the learners’ individual needs. Second, the deployment of e-learning, and therewith the freedom to design the appropriate kind of activities is bound by strict economical conditions, i.e. the amount of time available to staff to support the learning process. In this thesis two models have been developed and implemented that each address a different need. The first model covers the need to support the design task of staff, the second one the need to support the staff in supervising and giving guidance to students' learning activities. More specifically, the first model alleviates the design task by offering a set of connected design and runtime tools that facilitate adaptive e-learning. The second model alleviates the support task by invoking the knowledge and skills of fellow-students. Both models have been validated in near-real-world task settings

Joint Labor-Management Training Programs for Healthcare Worker Advancement and Retention

[Excerpt] Filling vacancies and retaining workers in shortage areas such as nursing and other allied health occupations remains a challenge in today’s healthcare industry. At the same time, low-wage workers in the healthcare industry often lack the educational credentials necessary to move into higher-paying occupations. This study seeks to understand the role of multi-employer joint labor-management healthcare worker training in meeting the needs of employers for career ladder advancement in their incumbent workforce. The study focuses on hospital employers and their experience with strategies for the advancement of low-wage and entry level workers into healthcare career pathways

A case study of agent programmability in an online learning environment

Software agents are well-suited to assisting users with routine, repetitive, and time-consuming tasks in various educational environments. In order to achieve complex tasks effectively, humans and agents sometimes need to work together. However, some issues in human agent interaction have not been solved properly, such as delegation, trust and privacy. The agent research community has focused on technologies for constructing autonomous agents and techniques for collaboration among agents. Little attention has been paid to supporting interactions between humans and agents. p* The objectives of this research are to investigate how easy it might be for a user to program his/her agent, how users behave when given the ability to program their agents, whether access to necessary help resources can be improved, and whether such a system can facilitate collaborative learning. Studying users’ concerns about their privacy and how an online learning environment can be built to protect users’ privacy are also interesting issues to us. In this thesis two alternative systems were developed for programmable agents in which a human user can define a set of rules to direct an agent’s activities at execution time. The systems were built on top of a multi-agent collaborative learning environment that enables a user to program his or her agent to communicate with other agents and to monitor the activities of other users and their agents. These systems for end user programmable agents were evaluated and compared. The result demonstrated that an end-user programming environment is able to meet users’ individual needs on awareness information, facilitate the information exchange among the users, and enhance the communication between users within a virtual learning environment. This research provides a platform for investigating concerns over user privacy caused by agent programmability