Kernel based neural networks with probabilistic reasoning are suitable for many practical applications. But in uence of data set sizes let the probabilistic approach fail in case of small data amounts. Possibilistic reasoning avoids this drawback because it is independent of class size. The fundamentals of possibilistic reasoning are derived from a probability/possibility consistency principle ...

Research on ontologies is becoming a popular topic in various branches of computer science. Their importance has been recognized in knowledge representation, natural language processing, knowledge management, multi-agent systems, intelligent integration of databases, cooperation of distributed applications, and web services. Among others, it gets a special accent and strong push in the context ...

A study was conducted to determine which better predicts performance among bank managers: tacit practical knowledge as assessed by the Tacit Knowledge Inventory for Managers (TKIM) or 2 psychometric measures of reasoning, the Raven's Advanced Progressive Matrices (Raven's) and the Verbal Reasoning subtest of the Differential Aptitude Test (DAT). Two hundred bank managers (43 experts and 157 non...

In this paper, we present PRACTIONIST (PRACTIcal reasONIng sySTem), a new framework built on the Bratman’s theory of practical reasoning to support the development of BDI agents in Java (using JADE) with a Prolog belief base. We aims at reducing the gap between the expressive power of the BDI model and the difficulty of efficiently implementing its features. In PRACTIONIST we adopt a goal-orien...

The standard notation for modelling software systems is the Unified Modelling Language (UML). This consists of a suite of mainly diagrammatic notations. However, UML’s constraint language, OCL, is entirely textual, making the notation less accessible to practitioners. The Reasoning with Diagrams project aims to build the foundation for more accessible notations for practitioners, building on an...

In intentional agents, actions are derived from the mental attitudes and their relationships. In particular, preferences (positive desires) and restrictions (negative desires) are important proactive attitudes which guide agents to intentions and eventually to actions. In this paper we overview recent developments about a multi-context based agent architecture g-BDI to represent and reasoning a...

Autonomous agents operating in a dynamic environment need constantly to reason about actions in pursuit of their goals, while taking into consideration possible norms imposed on those actions. Normative practical reasoning supports agents decision making about what is best for an agent to do in a given situation. What makes practical reasoning challenging is the conflict between goals that the ...

The Suggested Upper Merged Ontology (SUMO) has provided the TPTP problem library with problems that have large numbers of axioms, of which typically only a few are needed to prove any given conjecture. The LTB division of the CADE ATP System Competition tests the performance of ATP systems on these types of problems. The SUMO problems were used in the SMO category of the LTB division in 2008. T...

vi Acknowledgements vii

Reasoning about others, as performed by agents in order to coordinate their behaviours with those of others, commonly involves forming and updating beliefs about hidden system properties such as other agents’ mental states. In this paper we introduce the Expectation-Strategy-Behaviour (ESB) framework which provides a generic machinery for such practical social reasoning and can be easily couple...