Non-Monotonic Reasoning with Connectionist Networks using Coarse-Coded Representations

This paper, describes a connectionist fault-tolerant non-monotonic reasoning system, which uses coarse-coded distributed representations. Distributed representations are known to give the advantages of fault tolerance, generalization and graceful degradation of performance under noise conditions. A semantic network is designed, using a novel approach, with connectionist networks using coarse-coded representations to perform non-monotonic reasoning. The system performs non-monotonic reasoning using the property of inheritance. The system also supports the feature of cancellation of inheritance, whereby more specific information associated with the nodes lower in the ´isa´ hierarchy is given precedence over default information associated with the nodes higher in the hierarchy. System has exhibited good generalization ability on unseen test inputs. System´s performance with regard to its ability to exhibit fault tolerance under noise conditions is also studied. The system offers very good results of fault tolerance under noise conditions