Artificial general intelligence is a field of research aiming to distil the principles of intelligence that operate independently of a specific problem domain and utilise these principles in order to synthesise systems capable of performing any intellectual task a human being is capable of and beyond. While “narrow” artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition and robotic motion has shown impressive breakthroughs lately, understanding general intelligence remains elusive. We propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organisation. We call this process open-ended intelligence. Starting with a brief introduction of the current conceptual approach, we expose a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. Open-ended intelligence is then developed as an abstraction of the process of human cognitive development, so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organising network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values.

A significant motivation for programming language research is to find good abstractions and conceptual frameworks that enable us to understand and re* son about, certain kinds of complex computational phenomena in a simple way.In this paper we show that the specification of programs for the detection of stable properties of networks of communicating processes is facilitated -almost trivialized -in the framework of concurrent logic programming languages.We present the embedded short-circuit pr* gramming technique for detecting stable properties of networks, and illustrate its utility by providing a simple algorithm for distributed termination detection.We show that, the runtime behavior of a concurrent logic program incorporating this technique (for diffusing computations) is similar to the "DSA" scheme described in [7] for maintaining distributed counters.We modify the technique for repeated detection of quiescence for phased computations such as discrete simulations.We show that the abstraction can be mit nipulated without reference to its implementation by presenting a simple solution to the distributed knotdetection problem [IS].Finally we show that, under certain conditions, a simple extension allows repeated (live) snapshots [3] of the state of the computation to be taken almost trivially, thus providing another technique for detecting stable properties.