Reasoning about Action: An Argumentation - Theoretic Approach

We present a uniform non-monotonic solution to the problems of reasoning about action on the basis of an argumentation-theoretic approach. Our theory is provably correct relative to a sensible minimisation policy introduced on top of a temporal propositional logic. Sophisticated problem domains can be formalised in our framework. As much attention of researchers in the field has been paid to the traditional and basic problems in reasoning about actions such as the frame, the qualification and the ramification problems, approaches to these problems within our formalisation lie at heart of the expositions presented in this paper

Model-based learning for point pattern data

This article proposes a framework for model-based point pattern learning using point process theory. Likelihood functions for point pattern data derived from point process theory enable principled yet conceptually transparent extensions of learning tasks, such as classification, novelty detection and clustering, to point pattern data. Furthermore, tractable point pattern models as well as solutions for learning and decision making from point pattern data are developed

Epstein-Barr virus in gastric adenocarcinomas: association with ethnicity and CDKN2A promoter methylation

Aims: It has been shown previously (by immunohistochemistry) that gastric adenocarcinomas harbouring Epstein-Barr virus (EBV) frequently lose p16 protein. This study aimed to examine the mechanisms of inactivation of the CDKN2A gene and correlate the results with clinicopathological features

Variable caster steering in automotive dynamics

The tyre lateral force is a function of side slip and camber. While the lateral force due to side slip is the main part of the total cornering force, it saturates at a certain level of side slip angle even when the available tyre-road friction has not been fully utilised. In such a situation, the use of an appropriate extra camber could increase the safety, stability, and manoeuvrability of the car. This research serves as a further step to put the theory of variable caster steering into eect. The key idea of the theory is actively varying the caster to produce the required extra camber in a good fashion. In this investigation, the theory was examined in a specic case: developing a variable caster scheme to counteract roll camber - a phenomenon that generally limits the tyre lateral force and hence the maximum lateral acceleration of the car. By applying the variable caster scheme, the lateral force is increased. Therefore, the lateral grip capacity of the car is expanded. The benet of the variable caster was also further exploited to improve the steering returnability during low speed cornering. The theory of variable caster steering began with the development of road steering wheel kinematics. In order to do that, a number of coordinate systems was introduced to suciently describe the steering motion of a road steering wheel. The homogeneous transformation was then utilised to map coordinates between the systems. By doing so, the kinematics was developed. It was then used in two ways. The rst was to determine the camber, which is the orientation of the wheel, as a function of steering axis orientation, vehicle motion, suspension geometry, and steering angle, for a cornering car. The other was for developing a novel method to determine kingpin moment which aects the returnability of the steering wheels during low speed cornering. Then a rollable vehicle model, which is capable of capturing important characteristics of a turning car such as load transfer and roll motion, was constructed. The Magic Formula was used for tyre force modelling to take the camber contribution and the non-linear characteristics of the tyre into account. MATLAB/Simulink was used to simulate the dynamic response of the vehicle to steering input. The steering wheel kinematics and the dynamics model of the car were later validated using both multi-body and experimental data. More specically, the validation of the wheel kinematics was done by a road steering wheel model built in ADAMS software; the dynamic vehicle model was validated using data from eld tests and from a full car model constructed in the CarSim environment. A kinematics analysis of the camber function determined earlier was carried out. On the basis of the analysis, a scheme of varying the caster with the primary aim of countering the roll camber was proposed. The dynamic responses of the vehicle to dierent steering inputs were examined to evaluate its dynamic performance with and without the variable caster strategy. The simulation results show that the roll camber phenomenon, for the caster-controlled car, is reduced signicantly. The associated lateral acceleration and yaw rate increase without compromising other handling characteristics. The variable caster strategy, therefore, provides a more manoeuvrable car with expanded turning capacity compared to the passive car. To take advantage of the variable caster, a caster conguration that can improve the returnability of the steering wheels in low speed cornering manoeuvres was also suggested. Using the novel method for determining the kingpin moment, we showed that the caster conguration provides a better steering returnability during low speed cornering

Causal Strategic Learning with Competitive Selection

We study the problem of agent selection in causal strategic learning under multiple decision makers and address two key challenges that come with it. Firstly, while much of prior work focuses on studying a fixed pool of agents that remains static regardless of their evaluations, we consider the impact of selection procedure by which agents are not only evaluated, but also selected. When each decision maker unilaterally selects agents by maximising their own utility, we show that the optimal selection rule is a trade-off between selecting the best agents and providing incentives to maximise the agents' improvement. Furthermore, this optimal selection rule relies on incorrect predictions of agents' outcomes. Hence, we study the conditions under which a decision maker's optimal selection rule will not lead to deterioration of agents' outcome nor cause unjust reduction in agents' selection chance. To that end, we provide an analytical form of the optimal selection rule and a mechanism to retrieve the causal parameters from observational data, under certain assumptions on agents' behaviour. Secondly, when there are multiple decision makers, the interference between selection rules introduces another source of biases in estimating the underlying causal parameters. To address this problem, we provide a cooperative protocol which all decision makers must collectively adopt to recover the true causal parameters. Lastly, we complement our theoretical results with simulation studies. Our results highlight not only the importance of causal modeling as a strategy to mitigate the effect of gaming, as suggested by previous work, but also the need of a benevolent regulator to enable it.Comment: Corrected some in-text citation