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Internet-based scenarios, like co-working, e-freelancing, or crowdsourcing, usually need supporting collaboration among several actors that compete to service tasks. Moreover, the distribution of service requests, i.e., the arrival rate, varies over time, as well as the service workload required by each customer. In these scenarios, coalitions can be used to help agents to manage tasks they cannot tackle individually. In this paper we present a model to build and adapt coalitions with the goal of improving the quality and the quantity of tasks completed. The key contribution is a decision making mechanism that uses reputation and adaptation to allow agents in a competitive environment to autonomously enact and sustain coalitions, not only its composition, but also its number, i.e., how many coalitions are necessary. We provide empirical evidence showing that when agents employ our mechanism it is possible for them to maintain high levels of customer satisfaction. First, we show that coalitions keep a high percentage of tasks serviced on time despite a high percentage of unreliable workers. Second, coalitions and agents demonstrate that they successfully adapt to a varying distribution of customers' incoming tasks. This occurs because our decision making mechanism facilitates coalitions to disband when they become non-competitive, and individual agents detect opportunities to start new coalitions in scenarios with high task demand. © 2015 Elsevier Ltd. All rights reserved., The first author thanks the grant Formación de Profesorado Universitario (FPU), reference AP2010-1742. Arcos and Rodriguez-Aguilar thank projects COR (TIN2012-38876-C02-01/02) and Generalitat of Catalunya (2014 SGR-118). Work supported by the European Regional Development Fund (ERDF) and the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC)

Recent research underlines the important influence on consumer behavior of the mere presence of consumers on other consumers in retail businesses. While these results mainly relate to overall behavior, it is largely unknown how consumers behave in stores and how they react to customers present around them. This study examines the impact of an encounter between two consumers, directly in front of the same shelf row, on diverse consumer behavior. By means of two pilot studies we gained initial insights into the mutual influence. An image-based scenario study shows that the proximal distance is important for consumers' emotional state. In addition, the results indicate that these triggered negative and positive emotions mediate the effects of the distance on shopping satisfaction, aversive behavioral tendencies, willingness to buy, and number of alternatives considered.

Systems of autonomous and self-interested agents interacting to achieve individual and collective goals may exhibit undesirable or unexpected behaviour if left unconstrained. Norms have been widely proposed as a means of defining and enforcing societal constraints by using the deontic concepts of obligations, permissions and prohibitions to describe what must, may and should not be done, respectively. However, recent efforts to provide norm-enabled agent architectures that guide plan choices suffer from interfering with an agent?s reasoning process, and thus limit the agent?s autonomy more than is required by the norms alone. In this paper we describe an extension of the Beliefs-Desires-Intentions (BDI) architecture that enables normative reasoning used to help agents choose and customise plans taking norms into account. The paper makes three significant contributions: we provide a formal framework to represent norms compactly and to manage them; we present a formal characterisation of the normative positions induced by norms of an agent?s execution within a given time period; and finally, we put forth a mechanism for plan selection and ranking taking into consideration a set of normative restrictions.

Decision making is required by many tasks, such as shopping, nowadays assisted by software systems, and providing support to the decision making process is a feature that would significantly improve such systems. Many decision support systems and related approaches have been proposed to that purpose, but they often involve tedious elicitation processes or previously collected data. In this paper, we propose an automated decision making technique, which chooses an option from the set of those available based on preferences and priorities expressed in a high-level preference language, exploiting natural-language terms, such as expressive speech acts. Moreover, in order to make a decision, our technique goes beyond the provided preferences with psychology-inspired heuristics, which concern how humans make decisions, as provided preferences are typically not enough to resolve trade-offs among available options. Two studies were performed to evaluate our approach, and results indicate that our technique is effective both by comparing its recommendations with those made by a human expert, and by considering evaluation scores provided by users that experienced our technique. HighlightsDecision making technique that makes choices based on natural language based preferences.Exploitation of psychology-inspired heuristics in automated decision making.Evaluation performed through two studies, one offline using preferences of 113 participants and another online with 35 participants.

With continuing growth of the tourism industry over the past decades, the demand for interpretive experiences and education on marine wildlife tours has increased as well. Research showed that tourists expect an educational component on marine wildlife tours, but it remains somewhat vague what content tour participants expect. This study built on Luck's (2003) work and investigated participants on whale and dolphin tours in New Zealand with regards to the satisfaction with, and the desired educational content on these tours. Distributed questionnaires at two locations in New Zealand included closed-ended questions in Likert-type scale format, and open ended questions. Results show that tourists on whale and dolphin tours in New Zealand display high satisfaction rates, but also would like to learn more about wildlife and the sea in general. Results support the introduction of well-developed interpretation programmes on whale and dolphin tours.

Practical agent languages and their corresponding architectures have often relied on a static plan library with more or less direct trigger-response activation mechanisms as a source for agent behaviours for the sake of runtime efficiency. Although efficient, such a language design choice severely limits an agent's ability to reason about its goals and adapt to unforeseen circumstances after being deployed. This effectively delegates the task of planning to the designers themselves, who must design plan libraries able to cope with every foreseeable situation an agent might find itself in by designing plans to deal with any contingency. In this paper we develop a formal conversion process from traditional BDI agent languages into declarative planning. Using this conversion process, we show how to integrate domain independent planning algorithms into the BDI interpreter, allowing a designer to program an agent not only through the trigger-response mechanism used in traditional languages, but also in terms of declarative goals. Our contribution here is twofold: firstly we increase an agent's ability to cope with unforeseen situations and secondly we unburden an agent designer from having to define multiple plan combinations that could be easily generated by a planner.

Virtual organisations (VOs) are composed of a number of individuals, departments or organisations each of which has a range of capabilities and resources at their disposal. These VOs are formed so that resources may be pooled and services combined with a view to exploiting a perceived market niche. However, in the modern commercial environment it is essential to respond rapidly to changes in the market to remain competitive. Thus, there is a need for robust, agile, flexible systems to support the process of VO management. Within the CONOISE (www.conoise.org) project, agent-based models and techniques are being developed for the automated formation and maintenance of virtual organisations. In this paper we focus on the former, namely how an effective VO may be formed rapidly for a specified purpose.