An experiment with a three factorial design is described which tests the impact of 1) the degree of the mapping isomorphism, 2) the differences in the types of reasoning (deduction, induction, and analogy), and 3) the Icind of entities changed (objects, attributes, and relations) on the certainty of the inferences made. All the three factors have been found to have significant main effects and a significant interactions between the first factor and all the rest have also been found. Different particular results are discussed. For example, the certainty in the deductive inferences is not significantly different from the one in induction and analogy when there is no one-to-one mapping between the descriptions. Moreover, deduction, induction and analogy have similar behavior in relation to that factor. This is considered as a possible support of the existence of a uniform computational mechanism for evaluation of inferences in all the three kinds of reasoning, a mechanism which is primarily based on the degree of isomorphism.

Deduction, induction and analogy are considered as slightly different manifestations of one and the same reasoning process. A model of this reasoning process called associative memory-based reasoning is proposed. A computer simulation demonstrates that deduction, induction and analogy in problem solving could be performed by a single mechanism which combines the neural network approach with symbol level processing. Psychological experiments on priming effects in problem solving tasks have been carried out in order to test the hypothesis about the uniformity of human reasoning. In particular it has been shown that there are priming effects in all three cases (deduction, induction and analogy) and these priming effects decrease in the course of time which corresponds to the model's predictions based on the retrieval mechanism. The computer simulation demonstrates the same type of priming effects as observed in the psychological experiments.

Context-sensitivity is an important characteristic feature of every cognitive process and therefore should be reflected in every architecture pretending to explain human cognition. In this paper some experimental facts demonstrating context effects on various cognitive processes are reviewed and an attempt at context modeling is described A hybrid (symbolic/connectionist) cognitive architecture, DUAL , is proposed. It consists of a multitude of agents having both a symbolic and a connectionist part. The symbolic part represents some knowledge structure, while the coimectionist part represents its relevance to the current context The performance of the cognitive system emerges as result of the work and interaction of the currently active agents, where the set of active agents is not predefined for a specific task but is dynamic and reflects the specific context. So particular symbolic operations and data structures may be supported or suppressed depending on the particular activation pattern of the connectionist parts which represent the context-dependent relevance of the operations and structures. In this way a context-sensitive computation emerges. A n example of context-sensitive deductive reasoning is described.