We consider how to combine the preferences of multiple agents despite the presence of incompleteness and incomparability in their preference orderings. An agent’s preference ordering may be incomplete because, for example, there is an ongoing preference elicitation process. It may also contain incomparability, which can be useful, for example, in multi-criteria scenarios. We focus on the proble...

We demonstrate how supervised discriminative machine learning techniques can be used to automate the assessment of ‘English as a Second or Other Language’ (ESOL) examination scripts. In particular, we use rank preference learning to explicitly model the grade relationships between scripts. A number of different features are extracted and ablation tests are used to investigate their contribution...

This chapter introduces the concept of improving student memory retention using a distance learning tool by establishing the student’s communication preference and learning style before the student uses the module contents. It argues that incorporating a distance learning tool with an intelligent/interactive tutoring system using various components (psychometric tests, communication preference ...

Representing (and reasoning about) preference relations over combinatorial domains is computationally expensive. We argue that for many problems involving such preferences, it is relevant to simplify them by projecting them on a subset of variables. We investigate several possible definitions, focusing without loss of generality on propositional (binary) variables. We then define the notion of ...

Preference learning has recently received a lot of attention within the machine learning field, concretely learning by pairwise comparisons is a well-established technique in this field. We focus on the problem of learning the overall preference weights of a set of alternatives from the (possibly conflicting) uncertain and imprecise information given by a group of experts into the form of inter...

When faced with complex choices, users refine their own preference criteria as they explore the catalogue of options. In this paper we propose an approach to preference elicitation suited for this scenario. We extend Coactive Learning, which iteratively collects manipulative feedback, to optionally query example critiques. User critiques are integrated into the learning model by dynamically ext...

Robert Sugden has recently elaborated upon the case for a normative standard of freedom as “opportunity” that is supposed to cope with the problem of how to realign normative economics – with its traditional rational choice orientation – with behavioral economics. His standard, though, presupposes that people respond to uncertainty about their own future preferences by dismissing any kind of se...

For some multi-criteria decision aiding methods, the relative ranks of two actions may be inverted when the original set is altered. This phenomenon is known as rank reversal. In this contribution, we formalise rank reversal for the Promethee II method and derive the exact conditions for its occurrence when one ore more actions are added or removed from/to the original set. These conditions eve...

The objective of this study is to examine numerical evaluations the mosquito dispersal mathematical system (MDMS) in a heterogeneous atmosphere through artificial intelligence (AI) techniques via Bayesian regularization neural networks (BSR-NNs). MDMS constructed with six classes, i.e., eggs, larvae, pupae, host, resting mosquito, and ovipositional site densities-based ODEs system. computing BS...

There is lack of evidence on the black soldier fly (Hermetia Illucens L.) and its use as a biological control waste recycle agent. Unknown information related with mating ovipositional activities. The aim this research to determine reproductive profile manure Black Soldier Fly through different rearing substrate ruminant feed. A total 4 treatments replicates were used in experiment. treatment d...