The challenge of complexity for cognitive systems

Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

The challenge of complexity for cognitive systems

Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability Analysis

Feedback mechanisms are important in the analysis of vulnerability and resilience of social-ecological systems, as well as in the analysis of livelihoods, but how to evaluate systems with direct feedbacks has been a great challenge. We applied fuzzy cognitive mapping, a tool that allows analysis of both direct and indirect feedbacks and can be used to explore the vulnerabilities of livelihoods to identified hazards. We studied characteristics and drivers of rural livelihoods in the Great Limpopo Transfrontier Conservation Area in southern Africa to assess the vulnerability of inhabitants to the different hazards they face. The process involved four steps: (1) surveys and interviews to identify the major livelihood types; (2) description of specific livelihood types in a system format using fuzzy cognitive maps (FCMs), a semi-quantitative tool that models systems based on people’s knowledge; (3) linking variables and drivers in FCMs by attaching weights; and (4) defining and applying scenarios to visualize the effects of drought and changing park boundaries on cash and household food security. FCMs successfully gave information concerning the nature (increase or decrease) and magnitude by which a livelihood system changed under different scenarios. However, they did not explain the recovery path in relation to time and pattern (e.g., how long it takes for cattle to return to desired numbers after a drought). Using FCMs revealed that issues of policy, such as changing situations at borders, can strongly aggravate effects of climate change such as drought. FCMs revealed hidden knowledge and gave insights that improved the understanding of the complexity of livelihood systems in a way that is better appreciated by stakeholders

Personalize Wayfinding Information for Fire Responders based on Virtual Reality Training Data

Modern buildings with increasing complexity can cause serious difficulties for first responders in emergency wayfinding. While real-time data collection and information analytics become easier in indoor wayfinding, a new challenge has arisen: cognitive overload due to information redundancy. Standardized and universal spatial information systems are still widely used in emergency wayfinding, ignoring first responders’ individual difference in information intake. This paper proposes and tests the theoretical framework of a spatial information systems for first responders, which reflects their individual difference in information preference and helps reduce the cognitive load in line of duty. The proposed method includes the use of Virtual Reality (VR) experiments to simulate real world buildings, and the modeling of first responders’ reactions to different information formats and contents in simulated wayfinding tasks. This work is expected to set a foundation of future spatial information system that correctly and effectively responds to first responders’ needs

Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems

Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approaches—already partially considered by different disciplines—as well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions

UAV Operator mental workload:A neurophysiological comparison of mental workload and vigilance

Human Factors can offer insights into the nature of human performance across many different domains. The steady increase of unmanned systems presents not only a unique challenge in terms of defining the nature of human-system interaction, but also the demand for providing decision support systems to assist the human operate multiple of these systems, or indeed operate beyond line of visual sight. The nature of cognitive performance can involve a high degree of complexity and in many instances result in disagreement over what it is that is actually being measured. The main cognitive processes that tend to be discussed in terms of operating UAVs tends to focus on mental workload and situation awareness. However, other constructs, such as vigilance, may be considered as important when we examine the task of commanding a UAV – more so when a single operator is supervising multiple UAVs. This paper presents the findings of a study whereby participants were asked to perform tasks involving the control of a UAV. Neurophysiological assessment was carried out by application of functional near infra-red spectroscopy, and results are discussed in relation to how this technique can provide insight into higher cognitive functions related to UAV operator state

Emotions and the Engineering of Adaptiveness in Complex Systems

A major challenge in the engineering of complex and critical systems is the management of change, both in the system and in its operational environment. Due to the growing of complexity in systems, new approaches on autonomy must be able to detect critical changes and avoid their progress towards undesirable states. We are searching for methods to build systems that can tune the adaptability protocols. New mechanisms that use system-wellness requirements to reduce the influence of the outer domain and transfer the control of uncertainly to the inner one. Under the view of cognitive systems, biological emotions suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories to causally connect to the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress

Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework

In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactful recent contributions have been made possible through the integration of recent Machine Learning methods (based in particular on Deep Learning and Recurrent Neural Networks) with more traditional ones (e.g. Monte-Carlo tree search, goal babbling exploration or addressable memory systems). Regarding embodiment, we note that the traditional benchmark tasks (e.g. visual classification or board games) are becoming obsolete as state-of-the-art learning algorithms approach or even surpass human performance in most of them, having recently encouraged the development of first-person 3D game platforms embedding realistic physics. Building upon this analysis, we first propose an embodied cognitive architecture integrating heterogenous sub-fields of Artificial Intelligence into a unified framework. We demonstrate the utility of our approach by showing how major contributions of the field can be expressed within the proposed framework. We then claim that benchmarking environments need to reproduce ecologically-valid conditions for bootstrapping the acquisition of increasingly complex cognitive skills through the concept of a cognitive arms race between embodied agents.Comment: Updated version of the paper accepted to the ICDL-Epirob 2017 conference (Lisbon, Portugal

Organizational design: need for a socio-technical inclusive system design approach to meet 21st century workforce challenges

Changes occurring in the business and socio-economic global environments increase the complexity of working systems. The global workforce is becoming more diverse where people from different social, cultural, geographical and technical backgrounds work together in spite of their existing differences. Existence of varying human responses caused due to variations in individual’s physical, physiological, psychological, social and cognitive responses to the organizational design becomes a real challenge for designers. Moreover, increase in the number of older workers, also requires the attention of designers, as they are different in many ways. These issues increase the complexity of organizational systems and have serious implications for human factors and ergonomics as this complexity challenges the way conventional organizational systems are designed and implemented. There is a great need to develop new strategies where human variations are rightly understood and then emphasized during organizational design process. A proposed Sociotechnical Inclusive System Design approach has been discussed for addressing social and technical issues of organizational design by integrating socio-technical principles with inclusive thinking so that these challenges might be addressed at the organizational and individual levels. This article briefly describes global workforce challenges like increase in diversity, ageing, and impact of individual level variations on workplace safety and task performance. Finally, it highlights the need to design organizational systems based on diversity and differences where social and technical inclusivity should be an integral part of any design decision so that organizations can effectively utilize their human capital. The suggested design approach can draw multiple benefits including employee satisfaction, workplace safety and well-being, high productivity and quality and retention of a skilled workforce for a longer time. All these benefits ultimately support the attainment of long term organizational sustainability