Jörg Cassens

Explanation in Case-Based Reasoning---Perspectives and Goals

We present an overview of different theories of explanation from the philosophy and cognitive science communities. Based on these theories, as well as models of explanation from the knowledge-based systems area, we present a framework for explanation in case-based reasoning (CBR) based on explanation goals. We propose ways that the goals of the user and system designer should be taken into account when deciding what is a good explanation for a given CBR system. Some general types of goals relevant to many CBR systems are identified, and used to survey existing methods of explanation in CBR. Finally, we identify some future challenges.

Using activity theory to model context awareness

One of the cornerstones of any intelligent entity is the ability to understand how occurrences in the surrounding world influence its own behaviour. Different states, or situations, in its environment should be taken into account when reasoning or acting. When dealing with different situations, context is the key element used to infer possible actions and information needs. The activities of the perceiving agent and other entities are arguably one of the most important features of a situation; this is equally true whether the agent is artificial or not. This work proposes the use of Activity Theory to first model context and further on populate the model for assessing situations in a pervasive computing environment. Through the socio-technical perspective given by Activity Theory, the knowledge intensive context model, utilised in our ambient intelligent system, is designed.

Mapping goals and kinds of explanations to the knowledge containers of case-based reasoning systems

Research on explanation in Case-Based Reasoning (CBR) is a topic that gains momentum. In this context, fundamental issues on what are and to which end do we use explanations have to be reconsidered. This article presents a prelimenary outline of the combination of two recently proposed classifications of explanations based on the type of the explanation itself and user goals which should be fulfilled. Further on, the contribution of the different knowledge containers for modeling the necessary knowledge is examined.

Mental models of ambient systems: a modular research framework

This paper outlines our current research program in the fields of ambient intelligence and context-aware computing and the tools we are building to accomplish this research program. From a discussion of our conception of mental models in the domain of ambient context-aware computer systems we derive hypotheses which we intend to test empirically. A modular framework for implementing and assessing situation awareness in humans and computers is introduced. We describe the frameworks architecture and illustrate its suitability for its intended purpose. Finally, we present an outline of our next steps towards real world application systems for our research.

Explanations and context in ambient intelligent systems

Ambient intelligent systems are context aware by perceiving and reasoning about their environment, they perceive the needs of their users and proactively respond to these needs by being context sensitive. Users do not interact with these systems by traditional means only, but also through behavioural interfaces. This combination of mixed initiative systems and unconventional interfaces puts strong requirements on the explanatory capabilities of any system. The work presented here focuses on explaining the behaviour of an ambient intelligent systems to its users. It demonstrates how explanations can be combined with context to deal with the different types of explanations that are required for a meaningful interaction of a system and its users.

NEMO: the network environment for multimedia objects

In this article, we present the basic architecture of the Network Environment for Multimedia Objects (NEMO). NEMO is a smart media environment for contextualized, personalized, and device-specific interaction with multimedia objects. It provides its users access to interactive multimedia objects across a variety of computing platforms and devices, such as mobile phones, multi-touch tables, desktop computers and interactive whiteboards. NEMO Multimedia Objects are containers for metadata and media objects. Such media objects can be, for example, images, texts, animations, videos, audio files. Dedicated NEMO clients do not only offer means for presentation of media objects but also a runtime environment for applications on such objects. The system is suitable for application domains ranging from work environments to educational use and recreational activities.

User aspects of explanation aware CBR systems

This paper addresses the problem of embedding explanation-aware intelligent systems into a workplace environment. We outline an approach with three different perspectives, focusing on the work process as a whole as well as user interaction from an interface and a system view. The theoretical background consists of Actor Network Theory, Semiotics, and Activity Theory. We further propose to integrate this workplace analysis into a design process for knowledge-intensive and explanation-aware Case-Based Reasoning systems.

CASi - A Generic Context Awareness Simulator for Ambient Systems

In this paper, we present CASi (Context Awareness Simulator), a software system for the simulation of context-aware computer systems and environments. CASi provides an abstract framework of components for simulating smart world applications like a smart office or house with ambient sensors and actuators. Agents moving through these application worlds are tracked by sensors and their actions are influenced by actuators, both of which can be programmed to resemble the actual peripherals of the tested system. CASi allows testing ambient, context aware computer systems even in early stages of development without the need for expensive prototyping or real world deployment.

FACE – A Knowledge-Intensive Case-Based Architecture for Context-Aware Services

Technological progress has made it possible to interact with computer systems and applications anywhere and any time. It is crucial that these applications are able to adapt to the user, as a person, and to its current situation, whatever that is. Contextual information and a mechanism to reason about it have demonstrated an important potential to provide solutions in this respect. This paper aims at providing an integrated CBR architecture to be used in context-aware systems. It is the result of our work to develop ePH, a system for building dynamic user communities that share public interest information and knowledge that is accessible through always-on, context-aware services.

Modelling Behaviour Semantically

Context is only one of several strata of meaning and we can not predict realisation at the lexical or grammatical level from context alone. Yet, there is a tendency to confuse contextual patterning with semantic patterning and allocate patterning to the contextual level that might better be dealt with on other levels. While much work has been done on theorising lexis and grammar and, more recently, on seeing these in context, much remains to be done on theorising semantics as a separate level mediating between context and lexis and grammar. This paper examines the problem of modelling behaviour and the challenge of understanding behaviour in context as well as on a semantical level. By understanding the descriptive responsibilities allocated to each level of language, we are better able to see what remains to be covered by context within a model.