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This article employs regression techniques in order to gauge the relative importance of causal factors affecting the emergent behaviour of a hybrid dynamical system simulating human behaviour. Extending our previous work, in which the relative importance of causal factors was determined on the basis of classification into two discrete clusters, the target characteristic attribute of the simulation...
Reliability analysis of a logic network is considered in this paper. A logic network has some special properties that are not very common in reliability engineering. Firstly, the structure function of a logic network depends not only on the work of its components (logic gates), but also on the values of the input signals. Secondly, a logic network is a typical type of noncoherent system. These two...
This paper is a case study meant to demonstrate the relevance of causal summaries for exploratory analysis of human behaviour models. We broadly define a causal summary as a partition of the significant values of the analyzed variables (in our case the simulated motives fear and anger of human beings) into separate contributions by various “causing” factors, such as social influence or external events...
This paper outlines a general method for summarizing the behaviour of complex dynamic systems inspired by Bayesian causal analysis. The method is universally applicable and often permits to cut the backward causal loops through which the analyzed variables seem to co-determine themselves due to the nonlinearity of the equations describing complex systems.
In this article, which is a report of work in progress, we explore the principles of Bayesian causal analysis broadly along the lines formulated by Judea Pearl and other researchers. We apply these principles in the context of human behaviour modelling and aim at developing intelligent data analysis methods for large scale data sets, more specifically for logs from realistic simulations of human behaviour...
This article describes our work in progress and deals with methods and approaches for handling internal complexity emerging in highly realistic models of human behaviour. We present a new modelling approach to human decision making along with a conceptual design of several methods targeting selected aspects of complexity, such as the combinatorial explosion of action alternatives in rich environments,...
This article proposes a combination of object-oriented and ontology-based approaches for real-time interworking of human behaviour models in the context of agent-based simulation systems. We present a conceptual design of a semantic intermediation framework, including the split of the responsibilities between the intermediation ontology and software code. We illustrate our design in the context of...
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