AI-enabled Human-in-the-Loop Symbiotic Autonomous Systems: Towards Effective and Efficient Complex Problem Solving with robots, bots, chatbots…

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Abstract – We are concerned with the Symbiotic Autonomous Systems (SAS) meant as advanced intelligent information systems which involve a synergistic communication, cooperation and/or collaboration between the a broadly perceived autonomous systems, and a cognition based part, related to the human stakeholder. Notable examples can be robots, bots, chatbots, etc. which are meants to autonomously undertake some useful actions, usually in groups. First, we briefly clarify their specifics, mostly in the sense of having a physical form (robot) or not, just being pieces of software (bots), and also maybe using interaction with the human user (chatbots). Then, we advocate that the most effective and efficient way of using such autonomous systems, at least for the time being, is an active, or proactive, involvement of the human being, exemplified by the ‘Human-in-the-Loop’ architecture. Finally, we clarife the essence of the so-called 4C novel paradigm: communication, cooperation, coordination and collaboration.
This combination should guarantee an added value in terms of the effectiveness and efficiency of the systems’ operation and, above all, problem solving – which are the essence of the robot, bot or chatbot operations – in which a considerable part is related to decision making, also profitting from some added values implied by, for instance, some inspirations from psychology, cognitive sciences, decision sciences, etc. which is necessary in the case of the key role of the human being. Basically, we are concerned with an effective and efficient setting in which the human being is still a decisive stakeholder but he/she should be aided or supported by some additional „units”, humans (e.g. advisors) or „machines” (e.g. algorithms and computer systems). The human being should not be replaced but supported (augmented), at least for dealing with sophisticated tasks.
We first consider a seting when a human decision maker, who knows about the domain of his activities but not necessarily about solution tools, is aided by a domain expert who knows solution tools but not necessarily the domain; this can also be, e.g., a robot, bot or chatbot. We advocate the use of the judge-advisor type approaches. They are augmented with some AI (artificial intelligence) tools and techniques, notably machine learning models which can help find patterns and relationships governing the problem and thus efficient solution.
We also advocate the implementation of such a synergistic operation by employing a decision support system (DSS) to combine the power of the computer and the power of the humans, in the spirit of a socalled AI-enabled DSSs which employ advanced tools and techniques of AI (artificial intelligence) for the gathering and analysis of data and evidence, identification and diagnosis of problems, proposing courses of actions with their analyses, etc. This should help attain comprehensive and trustworthy procedures for a better joint operation of human with advanced robots, bots or chatbots that is crucial for virtually all modern compex problem solving.
Speaker(s): , Janusz Kacprzyk
Ruger Boskovik 18, Skopje, Macedonia, Macedonia

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