Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning

Social dilemmas have been widely studied to explain how humans are able to cooperate in society. Considerable effort has been invested in designing artificial agents for social dilemmas that incorporate explicit agent motivations that are chosen to favor coordinated or cooperative responses. The prevalence of this general approach points towards the importance of achieving an understanding of both an agent's internal design and external environment dynamics that facilitate cooperative behavior. In this paper, we investigate how partner selection can promote cooperative behavior between agents who are trained to maximize a purely selfish objective function. Our experiments reveal that agents trained with this dynamic learn a strategy that retaliates against defectors while promoting cooperation with other agents resulting in a prosocial society.Comment:

An efficient and versatile approach to trust and reputation using hierarchical Bayesian modelling

In many dynamic open systems, autonomous agents must interact with one another to achieve their goals. Such agents may be self-interested and, when trusted to perform an action, may betray that trust by not performing the action as required. Due to the scale and dynamism of these systems, agents will often need to interact with other agents with which they have little or no past experience. Each agent must therefore be capable of assessing and identifying reliable interaction partners, even if it has no personal experience with them. To this end, we present HABIT, a Hierarchical And Bayesian Inferred Trust model for assessing how much an agent should trust its peers based on direct and third party information. This model is robust in environments in which third party information is malicious, noisy, or otherwise inaccurate. Although existing approaches claim to achieve this, most rely on heuristics with little theoretical foundation. In contrast, HABIT is based exclusively on principled statistical techniques: it can cope with multiple discrete or continuous aspects of trustee behaviour; it does not restrict agents to using a single shared representation of behaviour; it can improve assessment by using any observed correlation between the behaviour of similar trustees or information sources; and it provides a pragmatic solution to the whitewasher problem (in which unreliable agents assume a new identity to avoid bad reputation). In this paper, we describe the theoretical aspects of HABIT, and present experimental results that demonstrate its ability to predict agent behaviour in both a simulated environment, and one based on data from a real-world webserver domain. In particular, these experiments show that HABIT can predict trustee performance based on multiple representations of behaviour, and is up to twice as accurate as BLADE, an existing state-of-the-art trust model that is both statistically principled and has been previously shown to outperform a number of other probabilistic trust models

Bootstrapping trust evaluations through stereotypes

Publisher PD

Delivering services by building and running virtual organisations

Non peer reviewedPostprin

Notorious places: image, reputation, stigma: the role of newspapers in area reputations for social housing estates

This paper reviews work in several disciplines to distinguish between image, reputation and stigma. It also shows that there has been little research on the process by which area reputations are established and sustained through transmission processes. This paper reports on research into the portrayal of two social housing estates in the printed media over an extended period of time (14 years). It was found that negative and mixed coverage of the estates dominated, with the amount of positive coverage being very small. By examining the way in which dominant themes were used by newspapers in respect of each estate, questions are raised about the mode of operation of the press and the communities' collective right to challenge this. By identifying the way regeneration stories are covered and the nature of the content of positive stories, lessons are drawn for programmes of area transformation. The need for social regeneration activities is identified as an important ingredient for changing deprived-area reputations

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

A Framework for Normative MultiAgent Organisations

The social and organisational aspects of agency have led to a good amount of theoretical work in terms of formal models and theories. From these different works normative multiagent systems and multiagent organisations are particularily considered in this paper. Embodying such models and theories in the conception and engineering of proper infrastructures that achieve requirements of openness and adaptation, is still an open issue. In this direction, this paper presents and discusses a framework for normative multiagent organisations. Based on the Agents and Artifacts meta-model (A&A), it introduces organisational artifacts as first class entities to instrument the normative organisation for supporting agents activities within it