The complexity definition has appeared during analysis of visual structures perception. The binary model of visual impacts finding was essential here for a possibility of the general (abstract) research. The Abstract Complexity Definition is one of the research results. The definition meets intuitive complexity criterion and could be a common surface for all existing definitins of complexity.

1.1 - Background - page 17 1.2 - The Style of Approach - page 18 1.3 - Motivation - page 19 1.4 - Style of Presentation - page 20 1.5 - Outline of the Thesis - page 21..

It is argued that complexity is not attributable directly to systems or processes but rather to the descriptions of their `best' models, to reflect their difficulty. Thus it is relative to the modelling language and type of difficulty. This approach to complexity is situated in a model of modelling. Such an approach makes sense of a number of aspects of scientific modelling: complexity is not situated between order and disorder; noise can be explicated by approaches to excess modelling error; and (...) simplicity is not truth indicative but a useful heuristic when models are produced by a being with a tendency to elaborate in the face of error. (shrink)

A popular goal in psychological science is to understand human cognition and behavior in the ‘real-world.’ In contrast, researchers have typically conducted their research in experimental research settings, a.k.a. the ‘psychologist’s laboratory.’ Critics have often questioned whether psychology’s laboratory experiments permit generalizable results. This is known as the ‘real-world or the lab’-dilemma. To bridge the gap between lab and life, many researchers have called for experiments with more ‘ecological validity’ to ensure that experiments more closely resemble and generalize to the (...) ‘real-world.’ However, researchers seldom explain what they mean with this term, nor how more ecological validity should be achieved. In our opinion, the popular concept of ecological validity is ill-formed, lacks specificity, and falls short of addressing the problem of generalizability. To move beyond the ‘real-world or the lab’-dilemma, we believe that researchers in psychological science should always specify the particular context of cognitive and behavioral functioning in which they are interested, instead of advocating that experiments should be more ‘ecologically valid’ in order to generalize to the ‘real-world.’ We believe this will be a more constructive way to uncover the context-specific and context-generic principles of cognition and behavior. (shrink)

Some practical criteria for free-will are suggested where free-will is a matter of degree. It is argued that these are more appropriate than some extremely idealised conceptions. Thus although the paper takes lessons from philosophy it avoids idealistic approaches as irrelevant. A mechanism for allowing an agent to meet these criteria is suggested: that of facilitating the gradual emergence of free-will in the brain via an internal evolutionary process. This meets the requirement that not only must the choice of action (...) be free but also choice in the method of choice, and choice in the method of choice of the method of choice etc. This is directly analogous to the emergence of life from non-life. Such an emergence of indeterminism with respect to the conditions of the agent fits well with the `Machiavellian Intelligence Hypothesis' which posits that our intelligence evolved (at least partially) to enable us to deal with social complexity and modelling `arms races'. There is a clear evolutionary advantage in being internally coherent in seeking to fulfil ones goals and unpredictable by ones peers. To fully achieve this vision several other aspects of cognition are necessary: open-ended strategy development; the meta-evolution of the evolutionary process; the facility to anticipate the results of strategies; and the situating of this process in a society of competitive peers. Finally the requirement that reports of the deliberations that lead to actions need to be socially acceptable leads to the suggestion that the language that the strategies are developed within be subject to a normative process in parallel with the development of free-will. An appendix outlines a philosophical position in support of my position. (shrink)

The reductionist/holist debate seems an impoverished one, with many participants appearing to adopt a position first and constructing rationalisations second. Here I propose an intermediate position of pragmatic holism, that irrespective of whether all natural systems are theoretically reducible, for many systems it is completely impractical to attempt such a reduction, also that regardless if whether irreducible `wholes' exist, it is vain to try and prove this in absolute terms. This position thus illuminates the debate along new pragmatic lines, and (...) refocusses attention on the underlying heuristics of learning about the natural world. (shrink)

When modelling complex systems one can not include all the causal factors, but one has to settle for partial models. This is alright if the factors left out are either so constant that they can be ignored or one is able to recognise the circumstances when they will be such that the partial model applies. The transference of knowledge from the point of application to the point of learning utilises a combination of recognition and inference ­ a simple model of (...) the important features is learnt and later situations where inferences can be drawn from the model are recognised. Context is an abstraction of the collection of background features that are later recognised. Different heuristics for recognition and model formulation will be effective for different learning tasks. Each of these will lead to a different type of context. Given this, there are (at least) two ways of modelling context: one can either attempt to investigate the contexts that arise out of the heuristics that a particular agent actually applies (the `internal' approach); or (if this is feasible) one can attempt to model context using the external source of regularity that the heuristics exploit. There are also two basic methodologies for the investigation of context: a top-down (or `foundationalist') approach where one tries to lay down general, a priori principles and a bottom-up (or `scientific') approach where one can try and find what sorts of context arise by experiment and simulation. A simulation is exhibited which is designed to illustrate the practicality of the bottom-up approach in elucidating the sorts of internal context that arise in an artificial agent which is attempting to learn simple models of a complex environment. It ends with a plea for the cooperation of the AI and Machine Learning communities as both learning and inference is needed if context is to make complete sense. (shrink)

The reductionist/holist debate is highly polarised. I propose an intermediate position of pragmatic holism. It derives from two claims: firstly, that irrespective of whether all natural systems are theoretically reducible, for many systems it is utterly impractical to attempt such a reduction, and secondly, that regardless of whether irreducible 'wholes exist, it is vain to try and prove this. This position illuminates the debate along new pragmatic lines by refocussing attention on the underlying heuristics of learning about the natural world.

Two different reasons for using agents are distinguished: the `engineering' perspective and the `social simulation' perspective. It is argued that this entails some differences in approach. In particular the former will want to prevent unpredictable emergent features of their agent populations whilst the later will want to use simulation to study precisely this phenomena. A concept of `social embeddedness' is explicated which neatly distinguishes the two approaches. It is argued that such embedding in a society is an essential feature of (...) being a truly social agent. This has the consequence that such agents will not sit well within an `engineering' methodology. (shrink)