Meta-programming in logic programming
Meta-programming in logic programming
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Safe and sound: artificial intelligence in hazardous applications
Safe and sound: artificial intelligence in hazardous applications
Representing Uncertain Knowledge: An Artificial Intelligence Approach
Representing Uncertain Knowledge: An Artificial Intelligence Approach
Applications of Uncertainty Formalisms
Applications of Uncertainty Formalisms
Acceptability of arguments as `logical uncertainty'
ECSQARU '93 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Quantitative and Qualitative Approaches to Reasoning under Uncertainty in Medical Decision Making
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
The Belief-Desire-Intention Model of Agency
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
Understanding intelligent agents: analysis and synthesis
AI Communications
A Prescriptive Approach for Eliciting Imprecise Weight Statements in an MCDA Process
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
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Since Pascal introduced the idea of mathematical probability in the 17th century discussions of uncertainty and "rational" belief have been dogged by philosophical and technical disputes. Furthermore, the last quarter century has seen an explosion of new questions and ideas, stimulated by developments in the computer and cognitive sciences. Competing ideas about probability are often driven by different intuitions about the nature of belief that arise from the needs of different domains (e.g., economics, management theory, engineering, medicine, the life sciences etc). Taking medicine as our focus we develop three lines of argument (historical, practical and cognitive) that suggest that traditional views of probability cannot accommodate all the competing demands and diverse constraints that arise in complex real-world domains. A model of uncertain reasoning based on a form of logical argumentation appears to unify many diverse ideas. The model has precursors in informal discussions of argumentation due to Toulmin, and the notion of logical probability advocated by Keynes, but recent developments in artificial intelligence and cognitive science suggest ways of resolving epistemological and technical issues that they could not address.