Handling Incoming Beliefs

International audienceMost logic-based approaches to knowledge and belief change in artificial intelligence assume that when a new piece of information comes up, it should be merely added to the current beliefs or knowledge when this does not lead to inconsistency. This paper addresses situations where this assumption does not hold. The focus is on the construction of Boolean standard-logic knowledge and belief bases in this context. We propose an approach to handle incoming beliefs that can require some formulas reconstruction or a form of preemption to be performed

Using graphical models and multi-attribute utility theory for probabilistic uncertainty handling in large systems, with application to nuclear emergency management

Although many decision-making problems involve uncertainty, uncertainty handling within large decision support systems (DSSs) is challenging. One domain where uncertainty handling is critical is emergency response management, in particular nuclear emergency response, where decision making takes place in an uncertain, dynamically changing environment. Assimilation and analysis of data can help to reduce these uncertainties, but it is critical to do this in an efficient and defensible way. After briefly introducing the structure of a typical DSS for nuclear emergencies, the paper sets up a theoretical structure that enables a formal Bayesian decision analysis to be performed for environments like this within a DSS architecture. In such probabilistic DSSs many input conditional probability distributions are provided by different sets of experts overseeing different aspects of the emergency. These probabilities are then used by the decision maker (DM) to find her optimal decision. We demonstrate in this paper that unless due care is taken in such a composite framework, coherence and rationality may be compromised in a sense made explicit below. The technology we describe here builds a framework around which Bayesian data updating can be performed in a modular way, ensuring both coherence and efficiency, and provides sufficient unambiguous information to enable the DM to discover her expected utility maximizing policy

Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information

The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation

Embedding agents in business applications using enterprise integration patterns

This paper addresses the issue of integrating agents with a variety of external resources and services, as found in enterprise computing environments. We propose an approach for interfacing agents and existing message routing and mediation engines based on the endpoint concept from the enterprise integration patterns of Hohpe and Woolf. A design for agent endpoints is presented, and an architecture for connecting the Jason agent platform to the Apache Camel enterprise integration framework using this type of endpoint is described. The approach is illustrated by means of a business process use case, and a number of Camel routes are presented. These demonstrate the benefits of interfacing agents to external services via a specialised message routing tool that supports enterprise integration patterns

Mental Frames and Organizational Decision-making: Facing the Challenges of Change

Adjusting to the strategic, business and economic changes requires efficient decision-making procedures which can in turn be highly affected by the underlying mental frames that the leaders of the organization hold. This article examines the impact of these mental frames on decision-making with respect to a specific attribute of a decision-making process: the belief that a CEO of a co-operative holds regarding member commitment. The analysis develops a simple theoretical model that shows how the co-op CEO’s obsolete mental frame creates distortions on decision making that can have negative effects on co-op’s strategic decisions and its market share. The starting point of the analysis is the case of the Saskatchewan Wheat Pool (SWP) – a Canadian grain handling, agri-food processing and marketing company that had little success in adapting to the changing economic environment of the Canadian agriculture.Industrial Organization,

Monitoring and control of spacecraft systems using procedural reasoning

Research concerned with automating the monitoring and control of spacecraft systems is discussed. In particular, the application of SRI's Procedural Reasoning System (PRS) to the handling of malfunctions in the Reaction Control System (RCS) of NASA's Space Shuttle is examined. Unlike traditional monitoring and control systems, PRS is able to reason about and perform complex tasks in a very flexible and robust manner, somewhat in the manner of a human assistant. Using various RCS malfunctions as examples (including sensor faults, leaking components, multiple alarms, and regulator and jet failures), it is shown how PRS manages to combine both goal-directed reasoning and the ability to react rapidly to unanticipated changes in its environment. In conclusion, some important issues in the design of PRS are reviewed and future enhancements are indicated

Factors influencing employee perceptions in lean transformations

The purpose of the study was to investigate employee perceptions during a lean transformation1. The combination of case study and survey methodologies was used to define elements influencing the perceived lean success of shop floor employees. According to our findings, belief, commitment, work method and communication all have a considerable direct impact on workers’ perceptions of lean success. However, their effects are very different based on the scope and focus of changes that is influenced by process characteristics. Perceptions regarding successful lean transformation during a moderate reorganisation of the company’s welding plant, where mainly males work, are affected only by commitment and work method, whereas the deep reorganisation of the sewing plant (populated by female employees) is only influenced by belief and communication