The organisation of sociality: a manifesto for a new science of multi-agent systems

In this paper, we pose and motivate a challenge, namely the need for a new science of multi-agent systems. We propose that this new science should be grounded, theoretically on a richer conception of sociality, and methodologically on the extensive use of computational modelling for real-world applications and social simulations. Here, the steps we set forth towards meeting that challenge are mainly theoretical. In this respect, we provide a new model of multi-agent systems that reflects a fully explicated conception of cognition, both at the individual and the collective level. Finally, the mechanisms and principles underpinning the model will be examined with particular emphasis on the contributions provided by contemporary organisation theory

Modelling process knowledge in architectural design: A case-based approach

The paper presents on-going research aimed at the understanding and support of process knowledge in architectural design, from early and not sufficiently defined, to satisfactorily-defined phases. Today, technical, planning, management and environmental issues have created a scenario of such complexity that traditionally efficient control tools (e.g. technical manuals) are inadequate and there is a demand for new, integrated instruments to handle the decision process underlying architectural design. We assume design as a recursive and incrementally specified intentional planning activity, involving goals, constraints and their relationships. The essence of architectural design is thus encapsulated in the continual recursive transformation of the initial model, in order to map the desired state onto the enacted one. On the basis of this concept of design we describe the model of an environment aimed at progressively representing the enlarging space of acquired knowledge, and at supporting the designer's central role in the management of complexity

Reasons for (prior) belief in bayesian epistemology

Bayesian epistemology tells us with great precision how we should move from prior to posterior beliefs in light of new evidence or information, but says little about where our prior beliefs come from. It o¤ers few resources to describe some prior beliefs as rational or well-justi�ed, and others as irrational or unreasonable. A di¤erent strand of epistemology takes the central epistemological question to be not how to change one�s beliefs in light of new evidence, but what reasons justify a given set of beliefs in the �rst place. We o¤er an account of rational belief formation that closes some of the gap between Bayesianism and its reason-based alternative, formalizing the idea that an agent can have reasons for his or her (prior) beliefs, in addition to evidence or information in the ordinary Bayesian sense. Our analysis of reasons for belief is part of a larger programme of research on the role of reasons in rational agency (Dietrich and List 2012a,b).Bayesian epistemology, doxastic reasons, prior and posterior beliefs, principle of insu¢ cient reason, belief formation, belief change

Clinical guidelines as plans: An ontological theory

Clinical guidelines are special types of plans realized by collective agents. We provide an ontological theory of such plans that is designed to support the construction of a framework in which guideline-based information systems can be employed in the management of workflow in health care organizations. The framework we propose allows us to represent in formal terms how clinical guidelines are realized through the actions of are realized through the actions of individuals organized into teams. We provide various levels of implementation representing different levels of conformity on the part of health care organizations. Implementations built in conformity with our framework are marked by two dimensions of flexibility that are designed to make them more likely to be accepted by health care professionals than standard guideline-based management systems. They do justice to the fact 1) that responsibilities within a health care organization are widely shared, and 2) that health care professionals may on different occasions be non-compliant with guidelines for a variety of well justified reasons. The advantage of the framework lies in its built-in flexibility, its sensitivity to clinical context, and its ability to use inference tools based on a robust ontology. One disadvantage lies in its complicated implementation

Transfer Scenarios: Grounding Innovation with Marginal Practices

Transfer scenarios is a method developed to support the design of innovative interactive technology. Such a method should help the designer to come up with inventive ideas, and at the same time provide grounding in real human needs. In transfer scenarios, we use marginal practices to encourage a changed mindset throughout the design process. A marginal practice consists of individuals who share an activity that they find meaningful. We regard these individuals not as end-users, but as valuable input in the design process. We applied this method when designing novel applications for autonomous embodied agents, e.g. robots. Owners of unusual pets, such as snakes and spiders, were interviewed - not with the intention to design robot pets, but to determine underlying needs and interests of their practice. The results were then used to design a set of applications for more general users, including a dynamic living-room wall and a set of communicating hobby robots

Constraint rule-based programming of norms for electronic institutions

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OWL-POLAR : A Framework for Semantic Policy Representation and Reasoning

Peer reviewedPreprin

Standard State Space Models of Unawareness

The impossibility theorem of Dekel, Lipman and Rustichini has been thought to demonstrate that standard state-space models cannot be used to represent unawareness. We first show that Dekel, Lipman and Rustichini do not establish this claim. We then distinguish three notions of awareness, and argue that although one of them may not be adequately modeled using standard state spaces, there is no reason to think that standard state spaces cannot provide models of the other two notions. In fact, standard space models of these forms of awareness are attractively simple. They allow us to prove completeness and decidability results with ease, to carry over standard techniques from decision theory, and to add propositional quantifiers straightforwardly