PDE-based Facial Animation: Making the Complex Simple

YesDirect parameterisation is among the most widely used facial animation techniques but requires complicated ways to animate face models which have complex topology. This paper develops a simple solution by introducing a PDE-based facial animation scheme. Using a PDE face model means we only need to animate a group of boundary curves without using any other conventional surface interpolation algorithms. We describe the basis of the method and show results from a practical implementation.EPSR

Hex

The game hex has simple rules but complex game play. A computer program was used to analyze different boards. This yielded an interesting insight in making the optimal Hex program

Comparing Guessing Games with homogeneous and heterogeneous players: Experimental results and a CH explanation

We investigate the decisions of individuals in simple and complex environments. We use a version of the Guessing Game (Beauty-contest Game) as a vehicle for our investigation, employing mathematically talented students. We find that our subjects think in complex environments more carefully before making decisions. We rationalize our findings using the Cognitive Hierarchy (CH) model proposed by Camerer, Ho, and Chong (2002). We relate our results to the emerging literature on the decision making of collective actors.Guessing Game

The challenge of complexity for cognitive systems

Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

A new construction of Lagrangians in the complex Euclidean plane in terms of planar curves

We introduce a new method to construct a large family of Lagrangian surfaces in complex Euclidean plane by means of two planar curves making use of their usual product as complex functions and integrating the Hermitian product of their position and tangent vectors. Among this family, we characterize minimal, constant mean curvature, Hamiltonian stationary, solitons for mean curvature flow and Willmore surfaces in terms of simple properties of the curvatures of the generating curves. As an application, we provide explicitly conformal parametrizations of known and new examples of these classes of Lagrangians in complex Euclidean plane.Comment: 15 pages, 5 figure

Clinical experience as evidence in evidence-based practice

Background. This paper's starting point is the recognition (descriptive not normative) that, for the vast majority of day-to-day clinical decision-making situations, the 'evidence' for decision-making is experiential knowledge. Moreover, reliance on this knowledge base means that nurses must use cognitive shortcuts or heuristics for handling information when making decisions. These heuristics encourage systematic biases in decision-makers and deviations from the normative rules of 'good' decision-making. Aims. The aim of the paper is to explore three common heuristics and the biases that arise when handling complex information in clinical decision-making (overconfidence, hindsight and base rate neglect) and, in response to these biases, to illustrate some simple techniques for reducing the negative influence of heuristics. Discussion. Nurses face a limited range of types of uncertainty in their clinical decisions and draw primarily on experiential knowledge to handle these uncertainties. This paper argues that experiential knowledge is a necessary but not sufficient basis for clinical decision-making. It illustrates how overconfidence in one's knowledge base, being correct 'after the event' or with the benefit of hindsight, and ignoring the base rates associated with events, conditions or health states, can impact on professional judgements and decisions. The paper illustrates some simple strategies for minimizing the impact of heuristics on the real-life clinical decisions of nurses. Conclusion. The paper concludes that more research knowledge of the impact of heuristics and techniques to combat them in nursing decisions is needed

Effects of communication and utility-based decision making in a simple model of evacuation

We present a simple cellular automaton based model of decision making during evacuation. Evacuees have to choose between two different exit routes, resulting in a strategic decision making problem. Agents take their decisions based on utility functions, these can be revised as the evacuation proceeds, leading to complex interaction between individuals and to jamming transitions. The model also includes the possibility to communicate and exchange information with distant agents, information received may affect the decision of agents. We show that under a wider range of evacuation scenarios performance of the model system as a whole is optimal at an intermediate fraction of evacuees with access to communication.Comment: 9 pages, 9 figure