probabilistic approach of traffic assignment has been primarily developed to provide a more realistic and flexible theoretical framework to represent traveler’s route choice behavior in a transportation network. the problem of path overlapping in network modelling has been one of the main issues to be tackled. due to its flexible covariance structure, probit model can adequately address the pro...

In general, the application of the meaning function T P to a normal logic program P results in innnite expressions and, hence, is infeasible in practice. On the other hand, the iteration of T P is of interest for several elds in AI. Therefore, we introduce a new representation of interpretations and adopt T P to this. The resulting function always results in nite expressions of tractable length...

The logistic normal distribution has recently been adapted via the transformation of multivariate Gaussian variables to model the topical distribution of documents in the presence of correlations among topics. In this paper, we propose a probit normal alternative approach to modelling correlated topical structures. Our use of the probit model in the context of topic discovery is novel, as many ...

This article describes a new theory of prepositional reasoning, that is, deductions depending on;/ or, and, and not. The theory proposes that reasoning is a semantic process based on mental models. It assumes that people are able to maintain models of only a limited number of alternative states of affairs, and they accordingly use models representing as much information as possible in an implic...

Players are unlikely to immediately play equilibrium strategies in complicated games or in games in which they do not have much experience playing. In these cases, players will need to learn to play equilibrium strategies. In laboratory experiments, subjects show systematic patterns of learning during a game. In psychological and economic models of learning, players tend to play a strategy more...