Continuous action system refinement

Action systems are a framework for reasoning about discrete reactive systems. Back, Petre and Porres have extended these action systems to continuous action systems, which can be. used to model hybrid systems. In this paper we define a refinement relation, and develop practical data refinement rules for continuous action systems. The meaning of continuous action systems is expressed in terms of a mapping from continuous action systems to action systems. First, we present a new mapping from continuous act ion systems to action systems, such that Back's definition of trace refinement is correct with respect to it. Second, we present a stream semantics that is compatible with the trace semantics, but is preferable to it because it is more general. Although action system trace refinement rules are applicable to continuous action systems with a stream semantics, they are not complete. Finally, we introduce a new data refinement rule that is valid with respect to the stream semantics and can be used to prove refinements that are not possible in the trace semantics, and we analyse the completeness of our new rule in conjunction with the existing trace refinement rules.

Reasoning algebraically about probabilistic loops

Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calculus. We extend their work to reasoning about probabilistic loops in the probabilistic refinement calculus. We apply our algebraic reasoning to derive transformation rules for probabilistic action systems. In particular we focus on developing data refinement rules for probabilistic action systems. Our extension is interesting since some well known transformation rules that are applicable to standard programs are not applicable to probabilistic ones: we identify some of these important differences and we develop alternative rules where possible. In particular, our probabilistic action system data refinement rules are new.

Linking job insecurity to negative decision making: The mediating role of job tension

Job insecurity has increased markedly in the developed economies of the world (Gray, 2002). The effects of job insecurity on individual employees and on organisational outcomes, however, are controversial. For instance, Greenhalgh and Rosenblatt (1984) point out that job insecurity can result in increased work effort, while Dekker and Schaufeli, (1995) argue that insecurity leads to stress and decreased performance. In this paper, we outline a study examining the indirect impact of job insecurity on decision-making, via job-related tension. Based on a web survey involving 217 participants, we found that job insecurity indirectly increased the adoption of negative decision-making strategies by increasing employees’ level of job-related tension. Limitations and implications for theory and managers are also discussed.

Investigating ontogenetic space with developmental cell lineages

Development plays a significant role in biological evolution, and is likely to prove an effective route to overcoming the limitations of direct genotype-phenotype mappings in artificial evolution. Nonetheless, the relationship between development and evolution is complex and still poorly understood. One question of current interest concerns the possible role that developmental processes may play in orienting evolution. A first step towards exploring this issue from a theoretical perspective is understanding the structure of ontogenetic space: the space of possible genotype-phenotype mappings. Using a quantitative model of development that enables ontogenetic space to be characterised in terms of complexity, we show that ontogenetic landscapes have a characteristic structure that varies with genotypic properties.