Abstract

This presentation concerns some idea of what could be done, in the author's view, to help make Wang's cognitive informatics a powerful and viable source of tools and techniques for solving various real life problems. First, we give a brief account of cognitive informatics meant as a multidisciplinary field within informatics, or computer science, that is based on results of cognitive and information sciences, and which deals with human information processing mechanisms and processes and their decision theoretic, engineering, etc. applications in broadly perceived computing. We focus on its purpose, i.e. to develop and implement technologies to facilitate and extend the information acquisition, comprehension and processing capacity of humans. Emphasis is on underlying processes in the brain. However, we advocate an extended approach in which though the very cognitive informatics is the foundation, as those processes in the brain are crucial, some sort of an “outer” cognitive informatics is needed which explicitly makes reference not what proceeds “internally” in the brain, because we do not “see” this, but “externally”, i.e. what people can see, judge, evaluate, etc., and what is clearly a result of cognitive information specific processes in the brain. This line of reasoning is in line with the very essence of comprehension, memorizing, learning, choice and decision making, satisfaction with partial truth, allowing for not perfect solutions, etc. dealt with using tools and techniques derived from many areas like psychology, behavioral science, neuroscience, artificial intelligence, linguistics, neuroeconomics etc. In our case, we will concentrate on some cognitive informatics type elements that mostly have been inspired by psychology and behavioral sciences, as our problem is inherently related to human judgments and perceptions, but we will mentioned some inspirations from neuroscience, notably along the lines of neuroeconomics. Cognitive informatics constitutes a foundation of its related new field, cognitive computing, which is basically a new direction in broadly perceived intelligent computing and systems that synergistically combines results from many areas, e.g., information science, computational sciences, computer science, artificial and computational intelligence, cybernetics, systems science, cognitive science, (neuro)psychology, brain science, linguistics, etc. to just mention a few. We try to show on an example of a dynamic systems modeling, more specifically scenario based regional development planning, that cognitive computing can provide new conceptual and implementation vistas. Basically, we consider a region that is characterized by 7 life quality indicators related to economic, social, environmental, etc. qualities, which evolve over some planning horizon due to some investments, mostly by some regional or governmental agencies. There are some scenarios of investment levels over the planning horizon, meant for the development of the particular life quality indexes, and some desired levels of these indexes, both objective, i.e. set by authorities, and subjective, i.e. perceived by the inhabitant groups. As a result of a particular investment scenario, the life quality indexes evolve over the planning horizon, and their temporal evolution is evaluated by the authorities and inhabitants. This evaluation has both an objective, i.e. against the “officially” set thresholds, and subjective, i.e. as perceived by various humans and their groups. Basically, we employ Kacprzyk's fuzzy dynamic programming based approach to the modeling and planning/programming of sustainable regional development, with soft constraints and goals, but we advocated a more sophisticated assessment of variability, stability, balancedness of consecutive investments. In this process we try to develop evaluation measures, and then the optimization type model using concepts that can be effectively and efficiently handled by cognitive computing, notably the inclusion of the so called decision making and behavioral biases, biases in probability and belief, social biases, memory errors, etc. Moreover, we strongly reflect the so called status quo and minimal change biases. By using many results from social sciences, psychology, behavioral economics, neuroeconomics, etc. on human judgments and human centric evaluations, we augment a traditional purely effectiveness and efficiency oriented analysis by a more sophisticated analysis of effects of variability of temporal evolution of some life quality indicators on the human perception of its goodness. The model presented, which has been employed for years as part of large mathematical modeling projects for sustainable regional development in many regions in Asia and Europe, is illustrated on an example with scenario analysis for a rural region plagued by social and economic difficulties in which subsidies should properly be distributed over time to obtain a best overall socioeconomic effect. In this talk we present the model in a different perspective, based first on the basic Wang's cognitive informatics and its Wang and Ruhe's decision making application, and then based on new, more comprehensive cognitive computing. We show that this provides a novel insight.

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