Multi-human decisionmaking: A control theoretic approach

The aim of this work is to discuss the relation between reliability of structural system and human performance of perception in man-machine system. It is studied to evaluate the effect of performance deterioration on structural safety from the viewpoint of uncertainties of human behavior. The subjective uncertainties are two kinds of uncertainties by designer and operator. From these points of view, the performance of operator on visual perception was investigated as a case study on visual task.

Decisionmaking functions in many large scale systems are distributed over multiple human decisionmakers who may have access to resources at different locations and are responsible for processing randomly arriving tasks. This leads to a complex team resource allocation and coordination problem. This paper presents a mathematical model and a solution methodology to investigate human team task processing behaviors based on a laboratory experiment. The problem at the current stage of investigation is formulated as a centralized scheduling problem involving multiple tasks and multiple platforms (vehicles equipped with resources). The geographical factors (e.g., locations and velocities) and combination of platforms for task processing are considered. A solution methodology is developed by combining decision tree and the concept of "attractiveness measure." This method is then applied to solve the experimental cases, and the solution methodology generates results similar to those obtained from the human experiment and captures human decisionmaking behaviors. Further model-dats comparison reveals several hidden tendencies in human team behavior, e.g., human teams adapts to tempo by speeding up resource usage but sacrificing efficiency. This model and solution methodology will be extending to a distributed case to resemble the coordination between team members, and a normative-descriptive model will be developed to analyze human decisionmaking.

A novel experimental paradigm, motivated by Naval tactical Command Control and Communication (C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) problems, is proposed that can be used to examine the general problem of how a team of humans "solve" problems of distributed resource management under uncertainty in a multi-task environment. Via the paradigm we can examine different organizational and informative structures, and different assignment of responsibility among the team members. The paradigm is highly amenable to analytic modeling, making it an excellent candidate for a research tool with which to develop normative-descriptive theories of team decision making.

Effects of agent timing on the human-agent team

* Emotions are largely absent in economic models. Possibly for this reason, many theories fail to explain the actual decisions made by managers. * Therefore, we integrate emotions with regular microeconomic theory. We focus on FDI decisions, and include both economic and emotional variables in our analysis of the firm's decision-making process. * In our theoretical analysis, emotions are included in a utility maximization model that considers not only the utility of the firm but also the utility of the individual decision-maker. * In our empirical analysis, the presence of emotions in FDI decision-making is tested using a sample of Dutch enterprises that considered an investment in Central or Eastern Europe between 1990 and 2000. Key Results * The empirical results show that emotions are important in economic decisionmaking. The presence of positive emotions increases the chance of Dutch firms to engage in an FDI in Central and Eastern Europe. Introduction Unlike Dr Spock cruising the Galaxy in his Voyager, most humans are not stripped of their emotions when making decisions. But equally most humans do not possess Dr. Spock's information processing capacities when making choices (Earl 2001). This is nevertheless how economic analysis models human decisions. Standard rational choice models and the bulk of empirical studies on microeconomic choice behavior use a rational choice model wherein little room is left for emotions to play a role, let alone a decisive one. The skills required to select and to handle the information that is needed to guarantee the rationality of the choice, are assumed to be abundantly available among human decision-makers. This assumption is not different in the study of foreign direct investment (FDI-) decisions. The complicated processes leading to a decision either to invest or not and where to invest (geographically) are notoriously difficult to model and the last thing that we need is more complication in terms of emotions playing a role. Direct investment-decisions are assumed to be based on estimates of the Net Present Values of all investment options and the final decision on whether or not to proceed with the investment in a particular country is assumed to be based on the ranking of all options (including the negative ones of not to invest) in terms of their estimated Net Present Value. When preparing a survey on investment-decisions of Dutch firms in Central and Eastern Europe and Central Asia. In open interviews with investors we explored the many reasons that might have played a role during open interviews with investors. During these discussions, approximately half of the respondents implied that "emotional" elements played a role in making final choices both regarding the decision to invest and the final choice of the country. Considerations such as the fact that the manager had participated in an exchange program during his/her study in that specific country, the fact that the partner of (one of) the owner(s) holds citizenship of the host country or that a personal acquaintance asked the Dutch firm to take over the foreign business, were among the important factors quoted to have been decisive elements in the decision process. These considerations seem far away from the algorithms of pure rational choice, but the question is whether they are. In this paper we explore theoretically how emotions can be seen as complements to rational choice processes and illustrate empirically that emotional factors do play a role in foreign direct investment-decisions. The second section includes a description of the economic decision-making literature including emotions and a frame that can be used to include emotions in investment-decisions. In section three a simple utility maximizing decision-making model will be described, with the specifications on how to include emotions. Section four provides empirical evidence that emotions are an influencing factor in the FDI-decision-making process, using the data from a survey among Dutch enterprises considering a foreign direct investment in Central and Eastern Europe. …

Human–agent teaming (HAT) is becoming more commonplace across industry, military, and consumer settings. Agents are becoming more advanced, more integrated, and more responsible for tasks previously assigned to humans. In addition, the dyadic human–agent teaming nature is evolving from a one–one pair to one–many, in which the human is working with numerous agents to accomplish a task. As capabilities become more advanced and humanlike, the best method for humans and agents to effectively coordinate is still unknown. Therefore, current research must start diverting focus from how many agents can a human manage to how can agents and humans work together effectively. Levels of autonomy (LOAs), or varying levels of responsibility given to the agents, implemented specifically in the decision-making process could potentially address some of the issues related to workload, stress, performance, and trust. This study sought to explore the effects of different LOAs on human–machine team coordination, performance, trust, and decision making in hand with assessments of operator workload and stress in a simulated multi-unmanned aircraft vehicle (UAV) intelligence surveillance and reconnaissance (ISR) task. The results of the study can be used to identify human factor roadblocks to effective HAT and provide guidance for future designs of HAT. Additionally, the unique impacts of LOA and autonomous decision making by agents on trust are explored.

In recent years, the concept of UAV (Unmanned Aerial Vehicle) swarm has been proposed and developed, which effectively solves the shortcomings of relatively small payload and relatively weak information perception processing capability in a single UAV operation. The research and application of UAV swarm technology has become an important direction of the development of UAV technology. UAV swarm not only can effectively improve the load capacity and information processing capacity through close cooperation between single UAV, but also has a high "self-healing" ability and strong robustness. However, due to the limited computing resources and complex external environment of UAVs, UAV swarm are vulnerable to forgery attacks, man-in-the-middle attacks and reply attacks. It is necessary to establish an authentication scheme to ensure the legitimate and reliable identity of UAVs for data exchange and sharing. However, traditional authentication schemes based on username, password or dynamic key have lower security levels, while RSA authentication requires a long session key and cannot meet the lightweight requirements in an UAV swarm. Based on the analysis and summary of existing authentication technologies and the special requirements of UAV swarm for cyber security, this paper puts forward an authentication scheme based on Zero Trust, achieves rapid authentication of UAV swarm in data exchange and sharing, and strengthens its ability to respond to cyber attacks.

This thesis introduces a model of empathy as a basis for helpful behaviour in teams consisting purely of artificial agents that collaborate on practical problem-solving tasks, and investigates whether the performance of such teams can benefit from empathic help between members as the analogy with human teams might suggest. Guided by existing models of natural empathy in psychology and neuroscience, it identifies the potential empathy factors for artificial agents, as well as the mechanisms by which they produce affective and behavioural responses. The performance of empathic agent teams situated in a microworld similar to the Coloured Trails game is studied through simulation experiments, with the model parameters optimized by a genetic algorithm. For low to moderate levels of random disturbance in the environment, empathic help is superior to random help, and it outperforms rational help as rational decision complexity grows, in particular at higher levels of environmental disturbance. --P. ii.

New methodologies and quantitative measurements for evaluating human-robot team performance must be developed to achieve effective coordination between teams of humans and unmanned vehicles. The Mixed Initiative Team Performance Assessment System (MITPAS) provides such a comprehensive measurement methodology. MITPAS consists of a methodology, tools and procedures to measure the performance of mixed manned and unmanned teams in both training and real world operational environments. This paper describes MITPAS and the results of an initial experiment conducted to validate the measures and gain insight into the effect of robot competence on operator trust as well as on human-robot team performance.

Biotechnical measurement and software system controlled features for determining the level of psycho-emotional tension on man–machine systems by fuzzy measures

For effective human-agent teaming, robots and other artificial intelligence (AI) agents must infer their human partner's abilities and behavioral response patterns and adapt accordingly. Most prior works make the unrealistic assumption that one or more teammates can act near-optimally. In real-world collaboration, humans and autonomous agents can be suboptimal, especially when each only has partial domain knowledge. In this work, we develop computational modeling and optimization techniques for enhancing the performance of human-agent teams, where both the human and the robotic agent have asymmetric capabilities and act suboptimally due to incomplete environmental knowledge. We adopt an online Bayesian approach that enables a robot to infer people's willingness to comply with its assistance in a sequential decision-making game. Our user studies show that user preferences and team performance vary with robot intervention styles, and our approach for mixed-initiative collaboration enhances objective team performance (p&lt;.001) and subjective measures, such as user's trust (p&lt;.001) and perceived likeability of the robot (p&lt;.001).

We describe the design and evaluation of Chaski, a robot plan execution system that uses insights from human-human teaming to make human-robot teaming more natural and fluid. Chaski is a task-level executive that enables a robot to collaboratively execute a shared plan with a person. The system chooses and schedules the robot's actions, adapts to the human partner, and acts to minimize the human's idle time.We evaluate Chaski in human subject experiments in which a person works with a mobile and dexterous robot to collaboratively assemble structures using building blocks. We measure team performance outcomes for robots controlled by Chaski compared to robots that are verbally commanded, step-by-step by the human teammate. We show that Chaski reduces the human's idle time by 85%, a statistically significant difference. This result supports the hypothesis that human-robot team performance is improved when a robot emulates the effective coordination behaviors observed in human teams.

A Man-Machine System Approach in the Field of Rehabilitation: A Challenge or a Necessity

An Approach of Dynamical Allocation of Supervision Tasks Between Man and Computer in Control Rooms of Automatized Production Systems

In an intelligent man-machine control system, control theory measures describing the operator's tracking performance can provide useful information concerning an operator's attentional slate. This information may be used to implement adaptive aiding procedures. Research is reviewed that relates attentional manipulations to variation in control theory parameters, and an experiment is then described in which 29 subjects performed a tracking task alone, and concurrently with a serial reaction-time task. Within the time-sharing condition, relative priorities between the two tasks were manipulated. The results are interpreted in terms of the separate effects of time-sharing and of priority manipulations upon measures of tracking gain, remnant, time-delay and response “holds,” and the feasibility of on-line measurement of those variables.