Ontologies play a key role in the advent of the Semantic Web. An important problem when dealing with ontologies is the modification of an existing ontology in response to a certain need for change. This problem is a complex and multifaceted one, because it can take several different forms and includes several related subproblems, like heterogeneity resolution or keeping track of ontology versions. As a result, it is being addressed by several different, but closely related and often overlapping research disciplines. Unfortunately, the boundaries of each such discipline are not clear, as the same term is often used with different meanings in the relevant literature, creating a certain amount of confusion. The purpose of this paper is to identify the exact relationships between these research areas and to determine the boundaries of each field, by performing a broad review of the relevant literature.

Multi-agent systems are complex systems in which multiple autonomous entities, called agents, cooperate in order to achieve a common or personal goal. These entities may be computer software, robots, and also humans. In fact, many multi-agent systems are intended to operate in cooperation with or as a service for humans. Typically, multi-agent systems are designed assuming perfectly rational, self-interested agents, according to the principles of classical game theory. Recently, such strong assumptions have been relaxed in various ways. One such way is explicitly including principles derived from human behavior. For instance, research in the field of behavioral economics shows that humans are not purely self-interested. In addition, they strongly care about fairness. Therefore, multi-agent systems that fail to take fairness into account, may not be sufficiently aligned with human expectations and may not reach intended goals. In this paper, we present an overview of work in the area of fairness in multi-agent systems. More precisely, we first look at the classical agent model, that is, rational decision making. We then provide an outline of descriptive models of fairness, that is, models that explain how and why humans reach fair decisions. Then, we look at prescriptive, computational models for achieving fairness in adaptive multi-agent systems. We show that results obtained by these models are compatible with experimental and analytical results obtained in the field of behavioral economics.

Semantic technologies promise to solve many challenging problems of the present Web applications. As they achieve a feasible level of maturity, they become increasingly accepted in various business settings at enterprise level. By contrast, their usability in open environments such as the Web—with respect to issues such as scalability, dynamism and openness—still requires additional investigation. In particular, Semantic Web services have inherited the Web service communication model, which is primarily based on synchronous message exchange technology such as remote procedure call (RPC), thus being incompatible with the REST (REpresentational State Transfer) architectural model of the Web. Recent advances in the field of middleware propose ‘semantic tuplespace computing’ as an instrument for coping with this situation. Arguing that truly Web-compliant Web service communication should be based, analogously to the conventional Web, on shared access to persistently published data instead of message passing, space-based middleware introduces a coordination infrastructure by means of which services can exchange information in a time- and reference-decoupled manner. In this article, we introduce the most important approaches in this newly emerging field. Our objective is to analyze and compare the solutions proposed so far, thus giving an account of the current state-of-the-art, and identifying new directions of research and development.

Computational social choice is a new discipline currently emerging at the interface of social choice theory and computer science. It is concerned with the application of computational techniques to the study of social choice mechanisms, and with the integration of social choice paradigms into computing. The first international workshop specifically dedicated to this topic took place in December 2006 in Amsterdam, attracting a mix of computer scientists, people working in artificial intelligence and multiagent systems, economists, game and social choice theorists, logicians, mathematicians, philosophers, and psychologists as participants.