# Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

## TL;DR

This study explores how human decision-making in multi-agent systems is affected by environmental uncertainty and time delays, using EEG to analyze cognitive processes.

## Contribution

The study introduces a novel framework combining system reliability, uncertainty types, and time delay effects on human decision-making in MAS.

## Key findings

- Unreliable system environments reduce memory load by minimizing system rule usage.
- Time delay does not significantly impact memory load during decision-making.
- EEG data reveals neural mechanisms involved in multiple-cue judgment under uncertainty.

## Abstract

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.