Analogical and Inductive Inference

Representing the spatial/kinematic domain and lattice computers.- A solution of the credit assignment problem in the case of learning rectangles.- Learning decision strategies with genetic algorithms.- Background knowledge and declarative bias in inductive concept learning.- Too much information can be too much for learning efficiently.- Some experiments with a learning procedure.- Unions of identifiable classes of total recursive functions.- Learning from multiple sources of inaccurate data.- Strong separation of learning classes.- Desiderata for generalization-to-N algorithms.- The power of probabilism in Popperian FINite learning.- An analysis of various forms of ‘jumping to conclusions’.- An inductive inference approach to classification.- Asking questions versus verifiability.- Predictive analogy and cognition.- Learning a class of regular expressions via restricted subset queries.- A unifying approach to monotonic language learning on informant.- Characterization of finite identification.- A model of the ‘redescription’ process in the context of geometric proportional analogy problems.- Inductive strengthening: The effects of a simple heuristic for restricting hypothesis space search.- On identifying DNA splicing systems from examples.