Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will show a problem appearing in this model caused by the use of a conditioning rule. We will also show that this problem can be avoided if undirected or compositional models are used instead.
The aphid parasitoid Aphidius ervi was collected and subsequently reared on Sitobion avenae on wheat or Acyrthosiphon pisum on alfalfa. Parasitoids from both origins were exposed in an olfactometer to alfalfa or wheat volatiles after plant experience (wheat or alfalfa) or after oviposition experience (S. avenae on wheat or A. pisum on alfalfa). The results showed the importance of adult experience, conditioning and innate preferences on the responses of A. ervi toward volatiles and provided a mechanistic explanation to the high prevalence of A. ervi on aphids on cereals and legumes in central Chile.
The knowledge of causal relations provides a possibility to perform predictions and helps to decide about the most reasonable actions aiming at the desired objectives. Although the causal reasoning appears to be natural for the human thinking, most of the traditional statistical methods fail to address this issue. One of the well-known methodologies correctly representing the relations of cause and effect is Pearl's causality approach. The paper brings an alternative, purely algebraic methodology of causal compositional models. It presents the properties of operator of composition, on which a general methodology is based that makes it possible to evaluate the causal effects of some external action. The proposed methodology is applied to four illustrative examples. They illustrate that the effect of intervention can in some cases be evaluated even when the model contains latent (unobservable) variables.
A possibilistic marginal problem is introduced in a way analogous to probabilistic framework, to address the question of whether or not a common extension exists for a given set of marginal distributions. Similarities and differences between possibilistic and probabilistic marginal problems will be demonstrated, concerning necessary condition and sets of all solutions. The operators of composition will be recalled and we will show how to use them for finding a T-product extension. Finally, a necessary and sufficient condition for the existence of a solution will be presented.
We determined if mature ladybirds use colour to initially find suitable host plants. We also determined whether ladybird beetles are capable of associating characteristics such as colour with the presence of prey. Here, we show that the multicoloured Asian ladybird beetle, Harmonia axyridis, has a differential response to yellow compared to green colours. Naive ladybirds, of both sexes, make significantly more visits and spend more time on yellow vs. green coloured pillars. After pairing yellow and green colours with the presence or absence of aphid prey, ladybirds alter their foraging behaviour. Beetles conditioned to having food on both pillar colours exhibited the same responses as naive beetles, while beetles conditioned to only yellow or green pillars did not exhibit a preference for visiting or spending time on different colours. However, there was a trend towards females spending more time on pillar colours on which they received reinforcement, and males spending more time foraging on colours opposite to that which they were reinforced. Thus, H. axyridis is capable of responding to cues such as colour, and its foraging behaviour can be altered as a result of prior experience.
The univariate conditioning of copulas is studied, yielding a construction method for copulas based on an a priori given copula. Based on the gluing method, g-ordinal sum of copulas is introduced and a representation of copulas by means of g-ordinal sums is given. Though different right conditionings commute, this is not the case of right and left conditioning, with a special exception of Archimedean copulas. Several interesting examples are given. Especially, any Ali-Mikhail-Haq copula with a given parameter λ > 0 allows to construct via conditioning any Ali-Mikhail-Haq copula with parameter μ \in [0,λ].