BEhavINg coGnitive Systems: Believable, Autonomous, Adaptive, Context Aware (BEINGS)

MENHIR is involved in the organization of the special session: BEhavINg coGnitive Systems: Believable, Autonomous, Adaptive, Context Aware (BEINGS) at the 1st IEEE International Conference on Human-Machine Systems, which will be held in Rome from 6th to 8th April 2020.


Anna Esposito, Università della Campania “Luigi Vanvitelli”, Italy.
Maria Inés Torres, Universidad País Vasco UPV/EHU, Spain
Zoraida Callejas Carrión, Universidad de Granada, Spain
Antonietta M. Esposito, Istituto Nazionale di Geofisica e Vulcanologia, Sez. di Napoli, Osservatorio Vesuviano, Italy.
Gennaro Cordasco, Università della Campania “Luigi Vanvitelli”, Italy
Sergio Escalera, Universitat de Barcelona and Computer Vision Center, Spain
Carl Vogel, Trinity College Dublin, School of Computer Science and Statistics, Ireland

The integration of cognitive theories, knowledge representation models and algorithms in a computational framework will enable rich models of human-machine interaction, and the development of novel machine learning techniques for the analysis of socially situated multimodal human communication streams. The successful analysis, modelling, and understanding of context effects on social interactions will be of high relevance for ICT applications where human-machine communication is particularly emphasized.
In order to enable the development of computational paradigms for implementing  socially believable, emotionally adaptive, and  context-aware systems (BEINGS) able to enhance quality of life in society, expertise in different yet complementary scientific fields must be accounted for. A holistic scientific approach, cross-cultural collaborations and exchanges are required. To this aim, this track is promoting contributions across a spectrum of disciplines reporting on  experimental data , theories, and mathematical models of dynamics of signal exchanges (in terms of shared meanings, emotional states, cultural differences, and cognitive processes of cooperation, and decision making). The ultimate goal is to equip machines with human level automaton intelligence.

Deadline: 20th January 2020


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