Improving Knowledge Management Programs Using Marginal Utility in a Metric Space Generated by Conceptual Graphs

Knowledge management has emerged as a field of endeavor that blends a systems approach with methods drawn from organizational management and learning. In contrast, knowledge representation, a branch of artificial intelligence, is grounded in formal methods. Research in the separate behavioral and the structural disciplines – knowledge management and knowledge engineering - has not traditionally cross-pollinated. This has prevented the development of many practical practices useful in organizations. Organization managers - line and senior - lack guidance in where to direct improvement efforts targeted at specific groups of company knowledge workers. Demonstrated here is Knowledge Improvement Measurement Space (KIMS), a model providing a solution to that improvement problem. It employs marginal utility theory in a metric space, with formal reasoning via software agents realized in Sowa\u27s conceptual graphs, operating over a knowledge management conceptual structure. These components allow repeated evaluation of knowledge improvement measurements. Knowledge representation technology was applied to organize and encourage knowledge sharing, to achieve competitive advantage, and to measure progress toward that achievement. The KlMS reentrant process, a method of using the KIMS model, was shown to consist of metrics data calculated by executing joined conceptual graphs, consolidated into a distance variable to be estimated via a Minkowski metrics space. The metric space was shown to be equivalent to a marginal utility, which may be evaluated to determine the new level of knowledge capability. The procedure may be repeated until knowledge management goals are achieved. The solution took into account the body of knowledge related human understanding and learning, and formal methods of knowledge organization. These were shown to include surface ontologies based in a knowledge management program, principles of business strategy, and organizational learning. KIMS was validated through a demonstration based on empirical data collected over a five-year program in a large aerospace company during its progress in applying the Software Engineering Institute Capability Maturity Model

Proceedings of the 18th Irish Conference on Artificial Intelligence and Cognitive Science

These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Technological University Dublin; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI)

Three Essays on Finance, Culture and Investor Behavior

This dissertation consists of three essays that examine the effects of corporate culture and investor psychology on corporate decisions and financial markets. The first essay focuses on the role of corporate culture in acquisitions, whereas the last two essays investigate deviations from market efficiency. The first essay uses textual analysis of firms annual reports to develop an estimate of the differences in corporate cultures of the combining firms, and finds that greater cultural differences between the firms lead to higher synergistic gains, but only when the acquirer has a stronger culture than its target. The synergy gains concentrate among deals where the acquirers values are not antagonistic to the targets. Further analysis of profitability and productivity (measured as earnings per employee) around the acquisition transaction corroborates these findings. Overall, the evidence suggests that differences in corporate culture are an important driver of announcement returns in mergers and acquisitions. The second essay investigates whether stock misvaluation drives industry-level merger waves by examining intra-wave patterns in acquirers valuation levels in a sample of acquisitions during 1981-2010. The essay contrasts two types of merger waves: stock waves defined on pure stock acquisitions, and cash waves formed on pure cash offers. Consistent with the misvaluation hypothesis, the essay finds that the occurrence of stock merger waves is tightly associated with industry stock valuation, and bidder stock valuation is negatively associated with long-run abnormal returns, especially so during waves of stock mergers. In contrast, there is little evidence of such patterns using the cash wave definition. The third essay investigates the effects of sunshine, wind, rain, snow, and temperature on daily index returns of 49 countries from 1973 to 2012. The paper finds pervasive weather effects that vary across temperature regions (cold, hot, and mild) and months. A hedge strategy that exploits the return predictability of daily weather generates up to 25% (11.8%) annualized out-of-sample gross (net) profits during 1993-2012. The systematic patterns of weather effects together with the relationship between their strength and timing and individuals seasonal propensity to spend time outdoors, suggest a plausible mechanism through which weather-induced mood influences index returns

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

IEEE/NASA Workshop on Leveraging Applications of Formal Methods, Verification, and Validation

This volume contains the Preliminary Proceedings of the 2005 IEEE ISoLA Workshop on Leveraging Applications of Formal Methods, Verification, and Validation, with a special track on the theme of Formal Methods in Human and Robotic Space Exploration. The workshop was held on 23-24 September 2005 at the Loyola College Graduate Center, Columbia, MD, USA. The idea behind the Workshop arose from the experience and feedback of ISoLA 2004, the 1st International Symposium on Leveraging Applications of Formal Methods held in Paphos (Cyprus) last October-November. ISoLA 2004 served the need of providing a forum for developers, users, and researchers to discuss issues related to the adoption and use of rigorous tools and methods for the specification, analysis, verification, certification, construction, test, and maintenance of systems from the point of view of their different application domains

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse