A Broad View of Intelligence: The Theory of Successful Intelligence.

This article reviews the theory of successful intelligence and attempts to construct-validate the theory of successful intelligence. It describes 4 distinct converging operations that have been used in these attempts. Two sets involve internal validation of the structure of the theory and 2 sets external validation of the theory with outside criteria. The internal validation operations involve information-processing (componential) analyses and both exploratory and confirmatory factor analyses. The external validation operations involve correlational analysis and analyses of instructional interventions based on the theory. The results are generally supportive of the theory and suggest that conventional conceptions of intelligence may be too narrow. The theory is of use in consulting because it broadens the scope of skills one looks for in seeking "intelligent" people for hiring, retention, and promotion and in assessing a person's ability to do his or her current job. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimal biocompatible solvent design for a two-stage extractive fermentation process with cell recycling

In this study, crisp and fuzzy multiple-goal optimization approaches are respectively introduced to design an optimal biocompatible solvent to a two-stage extractive fermentation with cell recycling for ethanol production. When designing a biocompatible solvent for the extractive fermentation process, many issues, such as extractive efficiency, conversion, amount of solvent utilized and so on, have to be considered. An interactive multiple-goal design procedure is introduced to determine a trade-off result in order to satisfy such contradicted goals. Both approaches could be iterated to solve the interactive multiple-goal design problem in order to yield a trade-off result. However, the crisp optimization design is a tedious task that requires the designer to provide various pairs of the upper bounds for the design problem to obtain the corresponding solution. The fuzzy optimization approach is able to be trade-off several goals simultaneously and to yield the overall satisfactory grade for the product/process design problem.     

Plasticity of feature-based selection in triple-conjunction search.

Two experiments examined the disruption of feature-based selection in triple-conjunction search at multiple target transfers. In Experiment 1, after 10 training sessions, a new target possessing previous distractor features was introduced. This produced disruption in RT and fixation number, but no disruption in feature-based selection. Specifically, there was a tendency to fixate objects sharing the target's contrast polarity and shape and this did not change even upon transfer to the new target. In Experiment 2, 30 training sessions were provided with three target transfers. At the first transfer, the results replicated Experiment 1. Subsequent transfers did not produce disruption on any measure. These findings are discussed in terms of strength theory, Guided Search, rule-based approaches to perceptual learning, and the area activation model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences.

Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate causes co-occurred with an effect. Evidence was presented in the form: AB→E; CA→E; AD→E; and so forth. In 1 story, all variables came from the same domain; in the other, the recurring candidate cause, A, came from a different domain (A was a psychological cause of a biological effect). After receiving this statistical evidence, children were asked to identify the cause of the effect on a new trial. Consistent with the predictions of a Bayesian model, all children were more likely to identify A as the cause within domains than across domains. Whereas 3.5-year-olds learned only from the within-domain evidence, 4- and 5-year-olds learned from the cross-domain evidence and were able to transfer their new expectations about psychosomatic causality to a novel task. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A fast evolutionary pursuit algorithm based on linearly combining vectors

In this paper, we propose a fast Evolutionary pursuit algorithm. It searches for optimal discriminant vectors through linearly combining standard bases. Experiments on the Yale and ORL databases verify its effectiveness and enhanced efficiency.     

Cubic Bézier approximation of a digitized curve

In this paper we present an efficient technique for piecewise cubic Bézier approximation of digitized curve. An adaptive breakpoint detection method divides a digital curve into a number of segments and each segment is approximated by a cubic Bézier curve so that the approximation error is minimized. Initial approximated Bézier control points for each of the segments are obtained by interpolation technique i.e. by the reverse recursion of De Castaljau's algorithm. Two methods, two-dimensional logarithmic search algorithm (TDLSA) and an evolutionary search algorithm (ESA), are introduced to find the best-fit Bézier control points from the approximate interpolated control points. ESA based refinement is proved to be better experimentally. Experimental results show that Bézier approximation of a digitized curve is much more accurate and uses less number of points compared to other approximation techniques.     

Emergence of communication in embodied agents evolved for the ability to solve a collective navigation problem

In this paper, we present the results of an experiment in which a collection of simulated robots that have been evolved for the ability to solve a collective navigation problem develop a communication system that allows them to co-operate better. The analysis of the results obtained indicates how evolving robots develop a non-trivial communication system and exploit different communication modalities. The results also indicate how the possibility of co-adapting the robots’ individual and social/communicative behaviour plays a key role in the development of progressively more complex and effective individuals.     

Implicit induction in conditional theories

We propose a new procedure for proof by induction in conditional theories where case analysis is simulated by term rewriting. This technique reduces considerably the number of variables of a conjecture to be considered for applying induction schemes. Our procedure is presented as a set of inference rules whose correctness has been formally proved. Moreover, when the axioms are ground convergent and the functions are completely defined, it is possible to apply the system for refuting conjectures. The procedure is even refutationally complete for conditional equations with Boolean preconditions over free constructors. The method is entirely implemented in the proverSPIKE. This system has solved interesting problems in a completely automatic way, that is, without interaction with the user and without ad hoc heuristics. It has also proved the challenging Gilbreath card trick, with only two easy lemmas.Preliminary versions of the results have been presented at the 13th International Joint Conference on Artificial Intelligence, Chambéry (France), 1993 (Bouhoula and Rusinowith, 1993).     

A novel data-driven approach to support decision-making during production scale-up of assembly systems

In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort.     

The Peer’s Dilemma: A general framework to examine cooperation in pure peer-to-peer systems

The exploration of social dilemmas is being considered a major foundation for encountering the enforced necessities of cooperation in self-organizing environments. Such environments are characterized by self-interested parties and the absence of trusted third parties. Recent approaches apply evolutionary socio-inspired games to formally prove the existence and further prolongation of cooperation patterns within communities. For instance, the Prisoner’s Dilemma game has thus provided a rich opportunity to examine self-interested behaviors in pure peer-to-peer networks. However, assuming a total absence of coalitions, incentives and punishment mechanisms, several works argue against a durable maintenance of cooperation neither at single-shot nor repeated-scenarios. In this article, we formally and experimentally demonstrate a counterexample for the latter by applying evolutionary game theory and a particular instance of the Rock–Scissors–Paper game. Our framework proves that the cyclic dominance of certain type of nodes within a P2P system has an impact and introduces a strategic aspect to the evolution of the overall community.