Computational philosophy of science
Computational philosophy of science
Induction and the discovery of the causes of scurvy: a computational reconstruction
Artificial Intelligence - Special issue on scientific discovery
Mutual online concept learning for multiple agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Abduction and induction: syllogistic and inferential perspectives
Abduction and induction: syllogistic and inferential perspectives
Recycling data for multi-agent learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
SMILE: Sound Multi-agent Incremental LEarning
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
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This paper proposes initial steps towards a generic framework for modeling the scientific process. It is generic according to two main axes. First, it can be instantiated to cover various types of inferences usually considered relevant in science, second, and more important here, it allows for the modeling of the social dimension of scientific activity. After motivating this drive for genericity by looking at some results from philosophy of science, the paper presents the bases of the framework and its central reliance on the notion of consistency, both at the individual and group levels. It then instantiates the social dimension of the framework by proposing an actor-critic model of scientific interaction. The ideas proposed are illustrated with examples of hypothesis formation in medicine.