A Connectionist Model for Constructive Modal Reasoning

Part of Advances in Neural Information Processing Systems 18 (NIPS 2005)

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Artur Garcez, Luis Lamb, Dov M. Gabbay


We present a new connectionist model for constructive, intuitionistic modal reasoning. We use ensembles of neural networks to represent in- tuitionistic modal theories, and show that for each intuitionistic modal program there exists a corresponding neural network ensemble that com- putes the program. This provides a massively parallel model for intu- itionistic modal reasoning, and sets the scene for integrated reasoning, knowledge representation, and learning of intuitionistic theories in neural networks, since the networks in the ensemble can be trained by examples using standard neural learning algorithms.