A CBR system needs a good case retention strategy to decide which cases to incorporate into the case base in order to maximize the performance of the system. In this work we present a collaborative case retention strategy, designed for multiagent CBR systems, called the Collaborative Case Bargaining strategy. The CCB strategy is a bargaining mechanism in which each CBR agent tries to maximize t...

Learning by observation allows a software agent to learn by watching an expert perform a task. This transfers the burden of training from the expert, who would traditionally need to program the agent, to the agent itself. Most existing approaches to learning by observation perform their observation in a purely passive manner. We propose a case-based reasoning agent that is able to observe passi...

Case-based Reasoning (CBR) is a mature technology for building knowledge-based systems that are capable to produce useful results even if no answer matches the query exactly. Often the result sets presented to users are ordered by means of similarity and utility. However, for complex applications with knowledge intensive domains we have discovered that results sets enriched by calculated simila...

Facial expression and hand gesture analysis plays a fundamental part in emotionally rich man-machine interaction (MMI) systems, since it employs universally accepted non-verbal cues to estimate the users’ emotional state. In this paper, we present a systematic approach to extracting expression related features from image sequences and inferring an emotional state via an intelligent rule-based s...

Knowledge-based recommenders support an easier comprehension of complex item assortments (e.g., financial services and electronic equipment). In this paper we show (1) how such recommenders can be developed in a Human Computation based knowledge acquisition environment (PEOPLEVIEWS) and (2) how the resulting recommendation knowledge can be exploited in a competition-based e-Learning environment...

This paper presents an integrative agent model for adaptive human-aware information presentation. Within the agent model, meant to support humans in demanding tasks, a domain model is integrated which consists of a dynamical model for human functioning, and a model determining the effects of information presentation. The integrative agent model applies model-based reasoning methods to the domai...

The objective of this study was to assess the response to location-based services (LBS) by three key demographic groups within the United Kingdom (UK). This study took the form of a survey of relevant demographics, attitudes and consumer behaviour undertaken via a webbased survey. Results are based on over 1200 respondents, filtered and segmented into three demographic groups who are typically ...

Determining the context of a feature (i.e., the factors aaect-ing the ranking of a feature within a case) has been subject of several studies in analysis tasks, particularly for classiication but not in synthesis tasks like planning. In this paper we will address this problem and explain how the domain theory plays a key role in determining the context of a feature. We provide a characterizatio...

The paper presents revocation schemes in role-based access control models. We are particularly interested in two key issues: how to perform revocation and how to manage the revocation policy. We show how to deal with these two aspects in the delegation model based on the OrBAC formalism and its administration licence concept. This model provides means to manage several delegation types, such as...