to stimulate the next wave of research on organization learning. It provides a conceptual framework for research on the differences and similarities of learning by individuals, groups, and organizations.

This study explores the premise that knowledge in new product development proves both a barrier to and a source of innovation. To understand the problematic nature of knowledge and the boundaries that result, an ethnographic study was used to understand how knowledge is structured differently across the four primary functions that are dependent on each other in the creation and production of a high-volume product. A pragmatic view of “knowledge in practice ” is developed, describing knowledge as localized, embedded, and invested within a function and how, when working across functions, consequences often arise that generate problematic knowledge boundaries. The use of a boundary object is then described as a means of representing, learning about, and transforming knowledge to resolve the consequences that exist at a given boundary. Finally, this pragmatic view of knowledge and boundaries is proposed as a framework to revisit the differentiation and integration of knowledge.

An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP hierarchically is described. By searching for aliased Markov sub-space regions based on the state variables the algorithm uses temporal and state abstraction to construct a hierarchy of interlinked smaller MDPs.

The aim of this research essay is to examine the structural nature of theory in information systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction and generalization that underlie an understanding of theory. A taxonomy is proposed that classifies information systems theories with respect to the manner in which four central goals are addressed: analysis, explanation, prediction and prescription. Five interrelated types of theory are distinguished: (i) theory for analysing; (ii) theory for explaining, (iii) theory for predicting; (iv) theory for explaining and predicting; and (v) theory for design and action. Examples illustrate the nature of each theory type. The applicability of the taxonomy is demonstrated by classifying a sample of journal articles. The paper contributes by showing that multiple views of theory exist and by exposing the assumptions underlying different viewpoints. In addition, it is suggested that the type of theory under development can influence the choice of an epistemological approach. Support is given for the legitimacy and value of each theory type. The building of integrated bodies of theory that encompass all theory types is advocated.

Adaptation to inversion of the visual eld is studied in a simple simulated model of phototactic behaviour. Inspired by recent ndings in neuroscience, a novel neural architecture based on continuous dynamical neural networks is implemented. Individual cells behave homeostatically by facilitating local plasticity whenever their activity goes out of bounds. Robots are evolved to perform long-term phototaxis on a series of light sources while trying to keep neurons behaving homeostatically. Robots are then tested under the condition of left/right inversion of vision. Initially, their phototactic capability is lost, which in most cases causes neurons to lose homeostasis and trigger plastic changes. After long periods of maladaptation, robots adapt to the new sensorimotor situation, and phototactic behaviour is recovered. The introduction of other disruptions such as radical perturbations to motor and sensor gains also results in eventual adaptation. The model intends t...

Many natural processes consist of networks of interacting elements which a ect each other's state over time, the dynamics depending on the pattern of connections and the updating rules for each element. Genomic regulatory networks are arguably networks of this sort. An attempt to understand genomic networks would bene t from the context of a general theory of discrete dynamical networks which is currently emerging. A key notion here is global dynamics, whereby state-space is organized into basins of attraction, objects that have only recently become accessible by computer simulation of idealized models 12;13, in particular \random Boolean networks". Cell types have been explained as attractors in genomic networks 5, where the network architecture is biased to achieve a balance between stability and adaptability in response to perturbation 3. Based on computer simulations using the software Discrete Dynamics Lab (DDLab) 15, these ideas are described, as well as order-chaos measures on typical trajectories that further characterize network dynamics. 1

orary issues: from philosophy of science, mathematics, and language; through systems, information, complexity, automata, and computer theory; and on to cognitive science; theoretical biology and the origins of life; biological and physical semiotics; chaotic dynamics, catastrophe theory and bifurcations; and self-reference, self-reproduction, and autopoiesis. The material is balanced between philosophical exposition and mathematical treatment and examples. The mathematical level is high conceptually but formally simple. Kampis draws from the latest results from the complete spectrum of the sciences, and is further able to relate and synthesize them together in terms of their implications. The content of the book extends across the whole spectrum of contemporary systems science as well, including extensive references. Therefore it may also be useful as a survey in systems science for advanced graduate students. There are, unfortunately, some significant problems in the text, which suffe

2 It is argued that complexity has only a lim ited use as a paradigm against reductionist approaches and that it has a much richer potential as a comparable property. What can complexity be usefully said to be a property of is discussed. It is argued that it is unlikely to have any useful value as applied to "real" objects or sy stems. Further that even relativising it to an observer has problems. It is proposed that complexity can usefully be applied only to constructions within a given language. It is argued that complexity is usefully differentiated from the concepts of size, ignorance, variety , minimum description length and order. A definition of complexity is proposed which can be summarised as "that property of a language expression which makes it difficult to formulate its overall behaviour even when given almost complete information about its atomic components and their inter-relations.". Some of the consequences of this definition are discussed. It is shown that...

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor --- a sequence of steps --- with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think.

Abstract Non-interference is typically used as a baseline security policy to formalize confidentiality of secret information manipulated by a program. In contrast to static checking of non-interference, this paper considers dynamic, automaton-based, monitoring of information flow for a single execution of a sequential program. The monitoring mechanism is based on a combination of dynamic and static analyses. During program execution, abstractions of program events are sent to the automaton, which uses the abstractions to track information flows and to control the execution by forbidding or editing dangerous actions. The mechanism proposed is proved to be sound, to preserve executions of well-typed programs (in the security type system of Volpano, Smith and Irvine), and to preserve some safe executions of ill-typed programs. 1