Prof. Jan TreurSocial AI Group, Vrije Universiteit Amsterdam, Netherlands
Speech Title: Modeling Multi-Order Adaptive Processes by Self-Modeling Networks
Abstract: This talk addresses the use of self-modeling networks to model adaptive biological, mental and social processes of any order of adaptation. A self-modeling network for some base network is a network extension that represents part of the base network structure by a self-model in terms of added network nodes and connections for them. A network structure in general involves network characteristics for connectivity (connections between nodes), aggregation (combining multiple incoming impacts on a node) and timing (node state dynamics speed). By representing some of these network characteristics by a self-model using dynamic node states, these characteristics become adaptive. By iterating this construction, multi-order network adaptation is easily obtained. A dedicated software environment for self-modeling networks that has been developed supports the modeling and simulation processes. This will be illustrated for some application domains, for example, for Cognitive Neuroscience by a second-order adaptive network model to model plasticity of connections and node excitability, and metaplasticity to control such plasticity.
More details, kindly refer to 'Modeling Multi-Order Adaptive Processes by Self-Modeling Networks'
Biography: Jan Treur works as a full professor in Artificial Intelligence. He is an internationally well-recognized expert in human-directed AI and cognitive and social modelling. The research of Jan Treur during the past 10 years concerns both fundamental and application-directed aspects of human-directed AI. This covers methods and techniques for modelling and analysis of human-directed AI approaches in a number of application areas, including Cognitive and Social modelling and simulation. He has been and still is active both by author and PC member roles in practically all relevant conferences and journals in these AI and application areas. Currently his research has mostly a multidisciplinary focus and addresses Network-Oriented Modeling approaches based on adaptive temporal-causal networks to model cognitive, affective and social interactions, with two books about this published in 2016 and 2020. Applications cover multi-order adaptive network models for mental and social simulation and human-aware or socially aware AI systems and virtual agents. More details can be found at URL https://www.researchgate.net/profile/Jan_Treur.