Towards a quantitative concession-based classification method of negotiation strategies

In order to successfully reach an agreement in a negotiation, both parties rely on each other to make concessions. The willingness to concede also depends in large part on the opponent. A concession by the opponent may be reciprocated, but the negotiation process may also be frustrated if the opponent does not concede at all.This process of concession making is a central theme in many of the classic and current automated negotiation strategies. In this paper, we present a quantitative classification method of negotiation strategies that measures the willingness of an agent to concede against different types of opponents. The method is then applied to classify some well-known negotiating strategies, including the agents of ANAC 2010. It is shown that the technique makes it easy to identify the main characteristics of negotiation agents, and can be used to group negotiation strategies into categories with common negotiation characteristics. We also observe, among other things, that different kinds of opponents call for a different approach in making concession

School tracking, social segregation and educational opportunity: evidence from Belgium

Educational tracking is a very controversial issue in education. The tracking debate is about the virtues of uniformity and vertical differentiation in the curriculum and teaching. The pro-tracking group claims that curriculum and teaching better aimed at children's varied interest and skills will foster learning efficacy. The anti-tracking group claims that tracking systems are inefficient and unfair because they hinder learning and distribute learning inequitably. In this paper we provide a detailed within-country analysis of a specific educational system with a long history of early educational tracking between schools, namely the Flemish secondary school system in Belgium. This is interesting place to look because it provides a remarkable mix of excellence and inequality. Indeed the Flemish school system is repeatedly one of the best performer in the international harmonized PISA tests in math, science and reading; whereas it produces some of the most unequal distributions of learning between schools and students. Combining evidence from the PISA 2006 data set at the student and school level with recent statistical methods, we show first the dramatic impact of tracking on social segregation; and then, the impact of social segregation on equality of educational opportunity (adequately measured). It is shown that tracking, via social segregation, has a major effect on inequality of opportunity. Children of different economic classes will have different access to knowledge.tracking, ability grouping, educational performance, social segregation, inequality, PISA

GOAL agents instantiate intention logic

Abstract. It is commonly believed there is a big gap between agent logics and computational agent frameworks. In this paper, we show that this gap is not as big as believed by showing that GOAL agents instantiate Intention Logic of Cohen and Levesque. That is, we show that GOAL agent programs can be formally related to Intention Logic. We do so by proving that the GOAL Verification Logic can be embedded into Intention Logic. It follows that (a fragment of) Intention Logic can be used to prove properties of GOAL agents. The work reported is an important step towards the application of standard tools from modal logic for e.g. model checking agent programs. Our results also prove useful for extending the expressiveness of the GOAL agent language. This is illustrated by incorporating temporally extended goals into GOAL agents.

The significance of bidding, accepting and opponent modeling in automated negotiation

Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we are able to study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively

The first automated negotiating agents competition (ANAC 2010)

Motivated by the challenges of bilateral negotiations between people and automated agents we organized the first automated negotiating agents competition (ANAC 2010). The purpose of the competition is to facilitate the research in the area bilateral multi-issue closed negotiation. The competition was based on the Genius environment, which is a General Environment for Negotiation with Intelligent multi-purpose Usage Simulation. The first competition was held in conjunction with the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10) and was comprised of seven teams. This paper presents an overview of the competition, as well as general and contrasting approaches towards negotiation strategies that were adopted by the participants of the competition. Based on analysis in post--tournament experiments, the paper also attempts to provide some insights with regard to effective approaches towards the design of negotiation strategies

Engineering Multiagent Systems - Reflections

This report documents the programme and outcomes of Dagstuhl Seminar 12342 ``Engineering multiagent Systems\u27\u27. The seminar brought together researchers from both academia and industry to identify the potential for and facilitate convergence towards standards for agent technology. As such it was particularly relevant to industrial research. A key objective of the seminar, moreover, has been to establish a road map for engineering multiagent systems. Various research areas have been identified as important topics for a research agenda with a focus on the development of multiagent systems. Among others, these include the integration of agent technology and legacy systems, component-based agent design, standards for tooling, establishing benchmarks for agent technology, and the development of frameworks for coordination and organisation of multiagent systems. This report presents a more detailed discussion of these and other research challenges that were identified. The unique atmosphere of Dagstuhl provided the perfect environment for leading researchers from a wide variety of backgrounds to discuss future directions in programming languages, tools and platforms for multiagent systems, and the road map produced by the seminar will have a timely and decisive impact on the future of this whole area of research

Design patterns for an interactive storytelling robot to support children's engagement and agency

In this paper we specify and validate three interaction design patterns for an interactive storytelling experience with an autonomous social robot. The patterns enable the child to make decisions about the story by talking with the robot, reenact parts of the story together with the robot, and recording self-made sound effects. The design patterns successfully support children's engagement and agency. A user study (N = 27, 8-10 y.o.) showed that children paid more attention to the robot, enjoyed the storytelling experience more, and could recall more about the story, when the design patterns were employed by the robot during storytelling. All three aspects are important features of engagement. Children felt more autonomous during storytelling with the design patterns and highly appreciated that the design patterns allowed them to express themselves more freely. Both aspects are important features of children's agency. Important lessons we have learned are that reducing points of confusion and giving the children more time to make themselves heard by the robot will improve the patterns efficiency to support engagement and agency. Allowing children to pick and choose from a diverse set of stories and interaction settings would make the storytelling experience more inclusive for a broader range of children