The Structure of Ill Structured Problems

The boundary between well structured and ill structured ~roblems is vague, fluid and not susceptible to formalization. Any problem solving process w'iii appear ill structured if the problem solver is a serial machine that has access to a ~w:-yiarge long-term memory of potentially relevant information, and]or access to a very large exterlm! memory that provides information about the actual real-world c~,sequences of problem-~olving actions. There is no reason to suppose that new and hitherto uaknown concepts or teckniques are needed to enable artificial intelligence systems to operate successfully in domains that have these characteristics

Ill-structured problems and the reference consultation: The librarian’s role in developing student expertise

Purpose – To apply the concept of ill-structured problems and learner expertise to the reference consultation. Design/methodology/approach – Research literature from the 1960s forward regarding ill-structured problems and learner expertise in a variety of disciplines was surveyed. Resulting characteristics of expert problem-solvers were used to suggest applications to the reference consultation. Findings – Librarians can structure the reference consultation to better meet students‟ needs as information problem solvers. Research limitations/implications – The method described appears to have sound basis in research into cognitive development and reflective thinking, but it has not been empirically demonstrated in the reference environment. Empirical research with reference librarians and students would be a logical next step. Originality/value – Research into ill-structured problems and learner expertise is ongoing in information retrieval systems. It has not been applied to the reference consultation

MULTIPLE AGENT FORMALISMS FOR COORDINATION IN ORGANIZATIONAL PROBLEMS

Many organizational problems are ill-structured where the structure of a problem is not apparent at the outset of the problem solving process. Agents responsible for these problems often decompose them into subproblems the solution of which is the responsibility of other agents. These problems are only nearly independent in the sense that temporal and technical dependencies exist between the different subproblems. Since the problems are interdependent, coordinating the activities of the different agents is important for ensuring that the partial solutions discovered by these different agents are not conflicting in terms of global consistency. Usual mechanisms for coordination include communication and negotiation between agents of interrelated problems. In this paper we describe a formalism for coordination in multiple agent ill-structured problems based on four properties of tasks, atomicity, serializability, completeness and soundness. We examine how these properties are essential for handling conflict resolution. We also outline some requirements for control.Information Systems Working Papers Serie

Sensemaking and metacognitive prompting in ill-structured problems

Purpose – The purpose of this paper is to develop a set of generic prompting principles and a framework of prompts that have the potential to foster learning and skill acquisition among adult novices when performing complex, ill-structured problems. Design/methodology/approach – Relevant research in the literatures surrounding problem structure, sensemaking, expertise, metacognition, scaffolding, and cognitive load were reviewed and synthesised in order to derive generic prompting principles and guidelines for their implementation. Findings – A framework of generic principles and prompts is proposed. Differentiation between prompts supporting cognition either within, or after an ill-structured problem-solving task was supported. Practical implications – Prompts such as those proposed in the framework developed presently can be designed into technology-enhanced learning environments in order to structure and guide the cognitive processes of novices. In addition, prompts can be combined with other learning support technologies (e.g. research diaries, collaborative discourse) in order to support learning. Empirical testing will be required to quantify the potential benefits (and limitations of) the proposed prompting framework. Originality/value – The prompts developed constitute a framework for structuring and guiding learning efforts in domains where explicit, actionable feedback is often unavailable. The proposed framework offers a method of tailoring the scaffolding of prompts in order to support differing levels of problem structure and may serve as the basis for establishing an internalised and adaptive learning approach that can be transferred to new problems or contexts

MULTIPLE AGENT FORMALISMS FOR COORDINATION IN ORGANIZATIONAL PROBLEMS

Many organizational problems are ill-structured where the structure of a problem is not apparent at the outset of the problem solving process. Agents responsible for these problems often decompose them into subproblems the solution of which is the responsibility of other agents. These problems are only nearly independent in the sense that temporal and technical dependencies exist between the different subproblems. Since the problems are interdependent, coordinating the activities of the different agents is important for ensuring that the partial solutions discovered by these different agents are not conflicting in terms of global consistency. Usual mechanisms for coordination include communication and negotiation between agents of interrelated problems. In this paper we describe a formalism for coordination in multiple agent ill-structured problems based on four properties of tasks, atomicity, serializability, completeness and soundness. We examine how these properties are essential for handling conflict resolution. We also outline some requirements for control.Information Systems Working Papers Serie

Design of a model-based expert-supported learning environment for problem solving expertise development

Conference Themes: Linking Knowing and Doing - Bridging the Gap between Theory and PracticeTeaching ill-structured problem solving skills is a critical and challenge task in medical education. While problem-base learning (PBL) is widely adopted in medical schools to enable students' learning with complex problems under minimal guidance, there are concerns about its effects on development of systemic knowledge structure and efficient reasoning process. To meet the challenge, a technology-enhanced learning environment is proposed in this study to improve students' expertise in complex problem solving by scaffolding their reasoning and knowledge construction processes with support of expert knowledge and model-based cognitive tools.published_or_final_versio

Blind Deconvolution Using A Regularized Structured Total Least Norm Algorithm

Rosen, Park and Glick proposed the structured total least norm (STLN) algorithm for solving problems in which both the matrix and the right-hand side contain errors. We extend this algorithm for ill-posed problems by adding regularization and use the resulting algorithm to solve blind deconvolution problems as encountered in image deblurring when both the image and the blurring function have uncertainty. The resulting regularized structured total least norm (RSTLN) algorithm preserves any affine structure of the matrix and minimizes the discrete L_p-norm error, where p=1,2, or infinity. We demonstrate the effectiveness of these algorithms for blind deconvolution