Abstract
Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has been observed in coupled electrical circuits, laser semi-conductors, and artificial neurons. Recent research indicates that the same process might also support the ability of humans to anticipate the occurrence of chaotic behavior in other individuals. Motivated by this latter work, the current study examined whether the process of feedback delay induced anticipatory synchronization could be employed to develop an interactive artificial agent capable of anticipating chaotic human movement. Results revealed that incorporating such delays within the movement-control dynamics of an artificial agent not only enhances an artificial agent’s ability to anticipate chaotic human behavior, but to synchronize with such behavior in a manner similar to natural human-human anticipatory synchronization. The implication of these findings for the development of human-machine interaction systems is discussed.
Highlights
Cyber-based social interaction and coordination has become increasingly ubiquitous in our society due to rapid advances in online social networking, interactive virtual-reality (VR) systems, and human-machine interaction (HMI)
In order to establish that participant-drivers and the AVA-response system exhibited chaotic movement dynamics during testing, we determined the Largest Lyapunov Exponent (LLE) for participant and AVA movement time series in each trial
The current study was designed to investigate whether the phenomenon of feedback delay induced anticipatory synchronization could be leveraged for adaptive HMI
Summary
Cyber-based social interaction and coordination has become increasingly ubiquitous in our society due to rapid advances in online social networking, interactive virtual-reality (VR) systems, and human-machine interaction (HMI). Effective cyber-based collaboration depends on the ability of both human and artificial agents to behave in a highly flexible and mutually responsive manner, constantly adapting to what each other is doing or will do next. HMI technologies are currently limited in the degree to which they can synchronize with and anticipate human actions during complex time-evolving behaviors [1,2,3,4]. The capabilities of interactive artificial agents are not currently comprehensive of the coordinative characteristics. Specific roles of the authors are articulated in the ‘author contributions’ section. Research partly supported by ARC Future Fellowship (FT180100447) awarded to Michael Richardson
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