Tipos de lógica utilizadas en la toma de decisiones estratégicas de marketing

Para el administrador el proceso de la toma de decisiones es uno de sus mayores retos y responsabilidades, ya que en su desarrollo se debe definir el camino más acertado en un sin número de alternativas, teniendo en cuenta los obstáculos sociales, políticos y económicos del entorno empresarial. Para llegar a la decisión adecuada no hay que perder de vista los objetivos y metas propuestas, además de tener presente el proceso lógico, detectando, analizando y demostrando el porqué de esa elección. Consecuentemente el análisis que propone esta investigación aportara conocimientos sobre los tipos de lógica utilizados en la toma de decisiones estratégicas al administrador para satisfacer las demandas asociadas con el mercadeo para que de esta manera se pueda generar y ampliar eficientemente las competencia idóneas del administrador en la inserción internacional de un mercado laboral cada vez mayor (Valero, 2011). A lo largo de la investigación se pretende desarrollar un estudio teórico para explicar la relación entre la lógica y la toma de decisiones estratégicas de marketing y como estos conceptos se combinan para llegar a un resultado final. Esto se llevara a cabo por medio de un análisis de planes de marketing, iniciando por conceptos básicos como marketing, lógica, decisiones estratégicas, dirección de marketing seguido de los principios lógicos y contradicciones que se pueden llegar a generar entre la fundamentación teórica

Skill Rating by Bayesian Inference

Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure.

Autonomous execution of tasks by swarm carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing system? The work reported in this paper is motivated towards bridging this gap by proposing swarm-array computing, a novel technique to achieve autonomy for distributed parallel computing systems. Among three proposed approaches, the second approach, namely 'Intelligent Agents' is of focus in this paper. The task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier. agents and can be seamlessly transferred between cores in the event of a pre-dicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed approach is validated on a multi-agent simulator.

Dynamic automata for mobile robot learning

Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.

Semantic-driven context-aware visual information indexing and retrieval: applied in the film post-production domain

A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the DREAM system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework. The use of the context- related collateral knowledge, represented by a novel probabilistic based visual keyword co-occurrence matrix, had been proven effective via the experiments conducted during system evaluation. The automatically generated semantic labels were fed into the Topic Map Engine which can automatically construct ontological networks using Topic Maps technology, which dramatically enhances the indexing and retrieval performance of the system towards an even higher semantic level.

3D path planning with novel multiple 2D layered approach for complex human-robot interaction

Navigating cluttered indoor environments is a difficult problem in indoor service robotics. The Acroboter concept, a novel approach to indoor locomotion, represents unique opportunity to avoid obstacles in indoor environments by navigating the ceiling plane. This mode of locomotion requires the ability to accurately detect obstacles, and plan 3D trajectories through the environment. This paper presents the development of a resilient object tracking system, as well as a novel approach to generating 3D paths suitable for such robot configurations. Distributed human-machine interfacing allowing simulation previewing of actions is also considered in the developed system architecture.