Artificial Empathy and Imprecise Communication in a Multi-Agent System
Source abstract
Abstract
This paper introduces a novel artificial intelligence model that integrates artificial empathy into the decision-making processes of collaborative agent systems. The existing models of collaborative behaviors, especially in swarm applications, lack the aspect of empathy, known to improve cooperation in human teams. Emphasizing both cognitive and emotional aspects of empathy, the introduced model navigates communication uncertainties and ambiguities, transforming these challenges into opportunities for learning and adaptation in dynamic environments. A significant feature of this model is its handling of imprecision through fuzzy logic, using fuzzy similarity measures in the decision process. The main objective of the presented research is to introduce a new model for improving cooperativeness in multi-agent systems with the use of cognitive empathy. Future research focus on implementing the model on physical platform and optimize the artificial empathy algorithms in the decision-making module.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cognitive Science and Mapping · Robotics and Automated Systems · Cognitive Computing and Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Artificial Intelligence, Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Uniwersytetu Poznańskiego 4, 61-614 Poznań, Poland
Institute of Robotics and Machine Intelligence, Faculty of Control, Robotics and Electrical Engineering, Poznań University of Technology, Piotrowo 3A, 60-965 Poznań, Poland
References (27)
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