An evidential approach to problem solving when a large number of knowledge systems is available

Some recent problems are no longer formulated in terms of imprecise facts, missing data or inadequate measuring devices. Instead, questions pertaining to knowledge and information itself arise and can be phrased independently of any particular area of knowledge. The problem considered in the present work is how to model a problem solver that is trying to find the answer to some query. The problem solver has access to a large number of knowledge systems that specialize in diverse features. In this context, feature means an indicator of what the possibilities for the answer are. The knowledge systems should not be accessed more than once, in order to have truly independent sources of information. Moreover, these systems are allowed to run in parallel. Since access might be expensive, it is necessary to construct a management policy for accessing these knowledge systems. To help in the access policy, some control knowledge systems are available. Control knowledge systems have knowledge about the performance parameters status of the knowledge systems. In order to carry out the double goal of estimating what units to access and to answer the given query, diverse pieces of evidence must be fused. The Dempster-Shafer Theory of Evidence is used to pool the knowledge bases

Complexity and Action: Reflections on Decision Making and Cybernetics.

This paper highlights some theoretical and epistemological reflections about the relevance of action for managerial studies. These reflections show how the cybernetic paradigm of complexity management can be used for better decision making that unites knowledge and action in a comprising, dynamic, and evolving approach. Cybernetics can help to overcome the fear of decision making in the face of uncertainty in complex scenarios, and can be an effective tool for improving the viability and competitiveness of firms in the twenty-first century

A Behavioral Approach to Learning in Economics - Towards an Economic Theory of Contingent Learning

In economics, adjustment of behavior has traditionally been treated as a "black box." Recent approaches that focus on learning behavior try to model, test, and simulate specific adjustment mechanisms in specific environments (mostly in games). Results often critically depend on distinctive assumptions, and are not easy to generalize. This paper proposes a different approach that aims to allow for more general conclusions in a methodologically more compatible way. It is argued that the introduction of the main determinants of learning behavior as situational restrictions into the standard economic model may be a fruitful way to capture some important aspects of human behavior that have often been omitted in economic theory. Based on a simple model of learning behavior (learning loop), robust findings from psychology are used to explain behavior adjustment, and to identify its determinants (contingent learning). An integrative methodology is proposed where the "black box" is not opened, but instead the factors that determine what happens inside, and the limits imposed by theses factors can be analyzed and used for model building. The paper concludes with testable hypotheses about learning behavior in the context of economics.microeconomics, game theory, learning theory, experiments

Education Reform at the "Edge of Chaos": Constructing ETCH (An Education Theory Complexity Hybrid) for an Optimal Learning Education Environment

EDUCATION REFORM AT THE "EDGE OF CHAOS":CONSTRUCTING ETCH (AN EDUCATION THEORY COMPLEXITY HYBRID) FOR AN OPTIMAL LEARNING EDUCATION ENVIRONMENT AbstractCurrently, the theoretical foundation that inspires educational theory, which in turn shapes the systemic structure of institutions of learning, is based on three key interconnected, interacting underpinnings -mechanism, reductionism, and linearity. My dissertation explores this current theoretical underpinning including its fallacies and inconsistencies, and then frames an alternative educational theoretical base - a hybrid complex adaptive systems theory model for education - that more effectively meets the demands to prepare students for the 21st century. My Education Theory Complexity Hybrid (ETCH) differs by focusing on the systemic, autopoietic nature of schools, the open, fluid processes of school systems as a dissipative structure, and nonlinearity or impossibility of completely predicting the results of any specific intervention within a school system.. In addition, I show how ETCH principles, when applied by educational system leaders, permit them to facilitate an optimal learning environment for a student-centered complex adaptive system.ETCH is derived from Complexity Theory and is a coherent, valid, and verifiable systems' framework that accurately aligns the education system with its goal as a student-centered complex adaptive system. In contrast to most dissertations in the School Leadership Program, which are empirical studies, mine explores this new theoretical orientation and illustrates the power of that orientation through a series of examples taken from my experiences in founding and operating the Lancaster Institute for Learning, a private state-licensed alternative high school in eastern Pennsylvania

Team Learning: A Theoretical Integration and Review

With the increasing emphasis on work teams as the primary architecture of organizational structure, scholars have begun to focus attention on team learning, the processes that support it, and the important outcomes that depend on it. Although the literature addressing learning in teams is broad, it is also messy and fraught with conceptual confusion. This chapter presents a theoretical integration and review. The goal is to organize theory and research on team learning, identify actionable frameworks and findings, and emphasize promising targets for future research. We emphasize three theoretical foci in our examination of team learning, treating it as multilevel (individual and team, not individual or team), dynamic (iterative and progressive; a process not an outcome), and emergent (outcomes of team learning can manifest in different ways over time). The integrative theoretical heuristic distinguishes team learning process theories, supporting emergent states, team knowledge representations, and respective influences on team performance and effectiveness. Promising directions for theory development and research are discussed