A note on knowledge-based programs and specifications

Knowledge-based program are programs with explicit tests for knowledge. They have been used successfully in a number of applications. Sanders has pointed out what seem to be a counterintuitive property of knowledge-based programs. Roughly speaking, they do not satisfy a certain monotonicity property, while standard programs (ones without tests for knowledge) do. It is shown that there are two ways of defining the monotonicity property, which agree for standard programs. Knowledge-based programs satisfy the first, but do not satisfy the second. It is further argued by example that the fact that they do not satisfy the second is actually a feature, not a problem. Moreover, once we allow the more general class of knowledge-based specifications, standard programs do not satisfy the monotonicity property either.Comment: To appear, Distributed Computin

Probabilistic Knowledge-Based Programs

International audienceWe introduce Probabilistic Knowledge-Based Programs (PKBPs), a new, compact representation of policies for factored partially observable Markov decision processes. PKBPs use branching conditions such as if the probability of ϕ is larger than p, and many more. While similar in spirit to value-based policies, PKBPs leverage the factored representation for more compactness. They also cope with more general goals than standard state-based rewards, such as pure information-gathering goals. Compactness comes at the price of reactivity, since evaluating branching conditions on-line is not polynomial in general. In this sense, PKBPs are complementary to other representations. Our intended application is as a tool for experts to specify policies in a natural, compact language, then have them verified automatically. We study succinctness and the complexity of verification for PKBPs

Debate as a tool for rehabilitation: a 8 week debate and public speaking course at Woodside Juvenile Rehabilitation Center

Sanction based prison approaches help to prevent crimes, but newer studies have shown that they do not prevent recidivism. Conversely, rehabilitation based programs have been shown to reduce recidivism rates, sparking a resurgence in these types of programs. Further, sanction based practices cost significantly more than rehabilitation programs that use parole. While rehabilitation programs are more effective and cheaper, more studies need to be performed to determine which type of rehabilitation program is the easiest and most effective. Preliminary studies show that education and CBT based programs are among the most effective. In order to add to the knowledge about education based approaches, we conducted an 8 week debate and public speaking intervention developed and organized by Jessica Bullock and SPEAK Inc. We hope to show that debate programs can provide valuable rehabilitation skills to students in prisons and help to reduce recidivism rates.https://scholarworks.uvm.edu/fmclerk/1306/thumbnail.jp

Eliciting Expertise

Since the last edition of this book there have been rapid developments in the use and exploitation of formally elicited knowledge. Previously, (Shadbolt and Burton, 1995) the emphasis was on eliciting knowledge for the purpose of building expert or knowledge-based systems. These systems are computer programs intended to solve real-world problems, achieving the same level of accuracy as human experts. Knowledge engineering is the discipline that has evolved to support the whole process of specifying, developing and deploying knowledge-based systems (Schreiber et al., 2000) This chapter will discuss the problem of knowledge elicitation for knowledge intensive systems in general

Coordinating Knowledge Work in Multi-Team Programs: Findings from a Large-Scale Agile Development Program

Software development projects have undergone remarkable changes with the arrival of agile development methods. While intended for small, self-managing teams, these methods are increasingly used also for large development programs. A major challenge in programs is to coordinate the work of many teams, due to high uncertainty in tasks, a high degree of interdependence between tasks and because of the large number of people involved. This revelatory case study focuses on how knowledge work is coordinated in large-scale agile development programs by providing a rich description of the coordination practices used and how these practices change over time in a four year development program with 12 development teams. The main findings highlight the role of coordination modes based on feedback, the use of a number of mechanisms far beyond what is described in practitioner advice, and finally how coordination practices change over time. The findings are important to improve the outcome of large knowledge-based development programs by tailoring coordination practices to needs and ensuring adjustment over time.Comment: To appear in Project Management Journa

The construction of knowledge-based economies versus knowledge societies: The cases of Germany and Singapore

In the past decades, terms such as knowledge-based economy (KBE)\u27, and \u27information/knowledge society\u27 have been adopted by governments worldwide in order to underline their interest in developing their economies and societies further and assure future growth. Many governments used these catchwords as labels for government programs and action plans aiming at economic and social prosperity. This aim of national governments to construct knowledge-based economies, information/knowledge societies, the actions taken and especially the ability or disability to do so, is the topic of this paper. As two cases of comparison act Singapore and Germany. (DIPF/Orig.

What Works at Scale? Distilling the Critical Success Factors for Scaling Up Rural Sanitation

This paper is based on the Knowledge Sharing Forum of the same name. It examines the conditions for success in sanitation programs and strategies that lead to robust implementation in various countries

Cognitive Styles and Adaptive Web-based Learning

Adaptive hypermedia techniques have been widely used in web-based learning programs. Traditionally these programs have focused on adapting to the user’s prior knowledge, but recent research has begun to consider adapting to cognitive style. This study aims to determine whether offering adapted interfaces tailored to the user’s cognitive style would improve their learning performance and perceptions. The findings indicate that adapting interfaces based on cognitive styles cannot facilitate learning, but mismatching interfaces may cause problems for learners. The results also suggest that creating an interface that caters for different cognitive styles and gives a selection of navigational tools might be more beneficial for learners. The implications of these findings for the design of web-based learning programs are discussed