Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness

This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas

When management encounters complexity

This paper aims at showing how management has come to encounter the sciences of complexity. Therefore the various levels and domains of management are outlined which leverage from the study of complexity. This is not, however, a descriptive study. Rather, we focus on how management can benefit from knowing of the sciences of complexity. New tools and rods, new languages and approaches are sketched that show a radical shift in management leading from a once dependent discipline from physics and engineering, towards a biologically and ecologically permeated new management.Whereas the main concern for complexity consists in understanding complex phenomena and systems, at the end a number of successful applications of complexity to management and entrepreneurial consulting are considered

Complex methods of inquiry: structuring uncertainty

Organizational problem spaces can be viewed as complex, uncertain and ambiguous. They can also be understood as open problem spaces. As such, any engagement with them, and any effort to intervene in order to pursue desirable change, cannot be assumed to be just a matter of ‘complicatedness’. The issue is not just a need to cope with dynamics of system. It is also the perceptual ‘boundedness’ of multitudes of assumptions about scope of whole and limitations of organization as system. Furthermore, explicit attention to complexities of feedback loops is an extremely important aspect of any systemic discussion. How can we help teams of competent professionals to engage purposefully with such uncertain and ambiguous problem domains? The author suggests that we can only address this effectively through pragmatic efforts to incorporate a multitude of boundary-setting assumptions, explored as part of active (self-) reflection and practical engagement. This must be undertaken without resorting to an overly simplistic application of convergent thinking in our efforts to support problem solving. Instead, we need to pursue divergent thinking and ‘complexification’ in our effort to support problem resolving. The main contribution of this thesis is to present a collection of principles that taken together, provide support for this engagement ntervention. A core feature of this result is the framework for Strategic Systemic Thinking, which includes examples of pragmatically useful methods and tools

OpenCog Hyperon: A Framework for AGI at the Human Level and Beyond

An introduction to the OpenCog Hyperon framework for Artificiai General Intelligence is presented. Hyperon is a new, mostly from-the-ground-up rewrite/redesign of the OpenCog AGI framework, based on similar conceptual and cognitive principles to the previous OpenCog version, but incorporating a variety of new ideas at the mathematical, software architecture and AI-algorithm level. This review lightly summarizes: 1) some of the history behind OpenCog and Hyperon, 2) the core structures and processes underlying Hyperon as a software system, 3) the integration of this software system with the SingularityNET ecosystem's decentralized infrastructure, 4) the cognitive model(s) being experimentally pursued within Hyperon on the hopeful path to advanced AGI, 5) the prospects seen for advanced aspects like reflective self-modification and self-improvement of the codebase, 6) the tentative development roadmap and various challenges expected to be faced, 7) the thinking of the Hyperon team regarding how to guide this sort of work in a beneficial direction ... and gives links and references for readers who wish to delve further into any of these aspects