Inference in classifier systems

Classifier systems (Css) provide a rich framework for learning and induction, and they have beenı successfully applied in the artificial intelligence literature for some time. In this paper, both theı architecture and the inferential mechanisms in general CSs are reviewed, and a number of limitations and extensions of the basic approach are summarized. A system based on the CS approach that is capable of quantitative data analysis is outlined and some of its peculiarities discussed

The motivating operation and negatively reinforced problem behavior. A systematic review.

The concept of motivational operations exerts an increasing influence on the understanding and assessment of problem behavior in people with intellectual and developmental disability. In this systematic review of 59 methodologically robust studies of the influence of motivational operations in negative reinforcement paradigms in this population, we identify themes related to situational and biological variables that have implications for assessment, intervention, and further research. There is now good evidence that motivational operations of differing origins influence negatively reinforced problem behavior, and that these might be subject to manipulation to facilitate favorable outcomes. There is also good evidence that some biological variables warrant consideration in assessment procedures as they predispose the person's behavior to be influenced by specific motivational operations. The implications for assessment and intervention are made explicit with reference to variables that are open to manipulation or that require further research and conceptualization within causal models

Learning sequences of rules using classifier systems with tags

IEEE International Conference on Systems, Man, and Cybernetics. Tokyo, 12-15 October 1999.The objective of this paper was to obtain an encoding structure that would allow the genetic evolution of rules in such a manner that the number of rules and relationship in a classifier system (CS) would be learnt in the evolution process. For this purpose, an area that allows the definition of rule groups has been entered into the condition and message part of the encoded rules. This area is called internal tag. This term was coined because the system has some similarities with natural processes that take place in certain animal species, where the existence of tags allows them to communicate and recognize each other. Such CS is called a tag classifier system (TCS). The TCS has been tested in the game of draughts and compared with the classical CS. The results show an improving of the CS performance

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

Engineering failure analysis and design optimisation with HiP-HOPS

The scale and complexity of computer-based safety critical systems, like those used in the transport and manufacturing industries, pose significant challenges for failure analysis. Over the last decade, research has focused on automating this task. In one approach, predictive models of system failure are constructed from the topology of the system and local component failure models using a process of composition. An alternative approach employs model-checking of state automata to study the effects of failure and verify system safety properties. In this paper, we discuss these two approaches to failure analysis. We then focus on Hierarchically Performed Hazard Origin & Propagation Studies (HiP-HOPS) - one of the more advanced compositional approaches - and discuss its capabilities for automatic synthesis of fault trees, combinatorial Failure Modes and Effects Analyses, and reliability versus cost optimisation of systems via application of automatic model transformations. We summarise these contributions and demonstrate the application of HiP-HOPS on a simplified fuel oil system for a ship engine. In light of this example, we discuss strengths and limitations of the method in relation to other state-of-the-art techniques. In particular, because HiP-HOPS is deductive in nature, relating system failures back to their causes, it is less prone to combinatorial explosion and can more readily be iterated. For this reason, it enables exhaustive assessment of combinations of failures and design optimisation using computationally expensive meta-heuristics. (C) 2010 Elsevier Ltd. All rights reserved

Division of Labour and Social Coordination Modes : A simple simulation model

This paper presents a preliminary investigation of the relationship between the process of functional division of labour and the modes in which activities and plans are coordinated. We consider a very simple production process: a given heap of bank-notes has to be counted by a group of accountants. Because of limited individual capabilities and/or the possibilities of mistakes and external disturbances, the task has to be divided among several accountants and a hierarchical coordination problem arises. We can imagine several different ways of socially implementing coordination of devided tasks. 1) a central planner can compute the optimal architecture of the system; 2) a central planner can promote quantity adjustments by moving accountants from hierarchical levels where there exist idle resources to levels where resources are insufficient; 3) quasi-market mechanisms can use quantity or price signals for promoting decentralized adjustments. By means of a simple simulation model, based on Genetic Algorithms and Classifiers Systems, we can study the dynamic efficiency properties of each coordination mode and in particular their capability, speed and cost of adaptation to changing environmental situations (i.e. variations of the size of the task and/or variations of agents' capabilities). Such interesting issues as returns to scale, specialization and workers exploitation can be easily studied in the same model

Addressing the underrepresentation of women in mathematics conferences

Despite significant improvements over the last few generations, the discipline of mathematics still counts a disproportionately small number of women among its practitioners. These women are underrepresented as conference speakers, even more so than the underrepresentation of women among PhD-earners as a whole. This underrepresentation is the result of implicit biases present within all of us, which cause us (on average) to perceive and treat women and men differently and unfairly. These mutually reinforcing biases begin in primary school, remain active through university study, and continue to oppose women's careers through their effects on hiring, evaluation, awarding of prizes, and inclusion in journal editorial boards and conference organization committees. Underrepresentation of women as conference speakers is a symptom of these biases, but it also serves to perpetuate them; therefore, addressing the inequity at conferences is valuable and necessary for countering this underrepresentation. We describe in detail the biases against women in mathematics, knowing that greater awareness of them leads to a better ability to mitigate them. Finally, we make explicit suggestions for organizing conferences in ways that are equitable for female mathematicians.Comment: 26 pages. See also "An annotated bibliography of work related to gender in science" (arXiv:1412.4104