Taro Kanno

A method for team intention inference

Recent advances in man-machine interaction include attempts to infer operator intentions from operator actions, to better anticipate and support system performance. This capability has been investigated in contexts such as intelligent interface designs and operation support systems. While some progress has been demonstrated, efforts to date have focused on a single operator. In large and complex artefacts such as power plants or aircrafts, however, a team generally operates the system, and team intention is not reducible to mere summation of individual intentions. It is therefore necessary to develop a team intention inference method for sophisticated team-machine communication. In this paper a method is proposed for team intention inference in process domains. The method uses expectations of the other members as clues to infer a team intention and describes it as a set of individual intentions and beliefs of the other team members. We applied it to the operation of a plant simulator operated by a two-person team, and it was shown that, at least in this context, the method is effective for team intention inference.

A model of team cognition based on mutual beliefs

This article proposes a generic model of team cognition based on mutual beliefs that provide foundations for the formulation of hypotheses and predictions concerning cognitive aspects of team interactions such as team situation awareness, team communication and cooperation, as well as human–agent interactions. The proposed model describes team cognition as a set of individual cognition (processes, states and mental constructs) and beliefs on the other members cognition and beliefs (mutual beliefs). One of the advantages of the introduction of the concept of mutual beliefs is that it can theoretically distinguish what is really shared among team members and what is only believed to be shared. This model also provides a framework to describe reasons and internal processes behind team interaction and communication in terms of team members cognitive status and mutual beliefs.

An evaluation method of team situation awareness based on mutual belief

Large and complex artifacts are usually operated by a team for its safety and efficiency, and breakdowns of team cooperation sometimes cause accidents. Studies of team cooperation therefore have been drawn attention from human factors and ergonomics researchers. Team situation awareness (TSA) has been regarded as one of the important topics in such team cooperation studies. Definitions of TSA in such studies are, however, mainly based on the perspective of observers. Some studies have pointed out that it is necessary to define TSA from the perspective of “belief” that team members possess in other members’ SA in order to capture the dynamics of team cooperation. In this study, evaluation indexes of TSA from both perspectives were proposed and they were compared with team performance. The results suggest that it is necessary to evaluate team SA not only from the perspective of observers but also from the perspective of beliefs.

Cognitive model of team cooperation in en-route air traffic control

Since controller teams are in charge of en-route air traffic control, team cooperation is a key issue for good control performance. We conducted ethnographic field observation at the Tokyo Area Control Center and then analyzed the obtained data to develop a cognitive model of team cooperation in en-route air traffic control. We segmented conversational records, behavioral records, and so on by control unit, and then clarified relations between the segments and identified expert knowledge and judgment behind them. Cognitive processes of controller teams were reconstructed based on a concept of distributed cognition. The analysis revealed that the mutual belief model is applicable to team cooperation processes, the role assignment of tasks within a controller team is implicit and that control plans are implemented smoothly once team situation awareness has been established. A cognitive model of controllers’ team cooperation has been constructed based on these findings.

Modeling and simulation of residents’ response in nuclear disaster

It is important to model and predict residents’ behaviors in an emergency in order to establish good evacuation schemes during disasters. This research presents modeling and simulation of residents’ behaviors in a nuclear disaster focusing on residents’ decision-making processes: information acquisition, situation assessment, and selecting actions. We selected qualitative causal relations between residents’ behaviors and the attributes of information, human, and situations from 57 reviews of the past 12 disaster cases. We then constructed a conceptual model of residents’ behaviors in a conventional stimulus–organism–response (S–O–R) model of human information processing. We adopted probabilistic reasoning (Bayesian belief network) to simulate the situation assessment of a resident in a nuclear disaster. We carried out a simulation using the announcement log of the JCO criticality accident and confirmed that the model could simulate the tendencies in residents’ behaviors observed in the actual disaster and can reflect various features of the conceptual model.

A distributed multi-agent simulation system for the assessment of disaster management systems

In order to design effective disaster emergency management systems, a number of factors, including not only accident/disaster phenomena but also human behaviours such as coordination and communication between different organisations, should be considered in an integrated and comprehensive manner. In this paper, we propose the basic design of MASTERD: a Multi-Agent Simulation sysTem of Emergency Response in Disasters. The chief characteristics of MASTERD are (1) its system extensibility, allowing for easy integration of various simulations, and (2) its behavioural simulation of many different individuals and organisations in emergency response. We present the development of a prototype of MASTERD for nuclear disasters and discuss possible applications of MASTERD for various social safety and security issues.

Team cognition model based on mutual beliefs and mental subgrouping

In this research, an extension of a dyadic (pair) team cognition model is proposed to describe the cognition of a team with more than two persons. This model provides a comprehensive framework for analysing the cognitive aspects of team interactions, such as team situation awareness, team memory, and human-agent interactions. One important aspect discussed in this research is a process called mental subgrouping. In a team with more than two persons, for each member to think of the other members as a single entity instead of several different individuals is natural. This behaviour is defined as mental subgrouping. By incorporating mental subgrouping into the mutual belief model, this research attempts to more accurately describe the cognition of a team from the perspective of both an outsider and the individual team members.

Effects of metacognition in cooperation on team behaviors

Traditional studies on measurements and training of teamwork have often focused on observational teamwork behaviors; however, measurements and training of unobservable teamwork such as mutual performance monitoring are also important for improving teamwork measurement and training. In addition, an improvement of cognitive mechanisms underlying teamwork must effectively be able to enhance team performance because sufficient situation awareness of status of team is expected to be a requirement for positive teamwork behaviors. This study focuses on metacognition in cooperation that underlies team cooperation and aims to investigate the importance of metacognition in cooperation by analyzing contents of reflection on cooperation collected in our previous study in terms of our proposed model about metacognition in cooperation. The comparisons of metacognition in cooperation elicited in a team experiment and team performance indexes suggest that an expansion of range of metacognition in cooperation by metacognitive instructions will enhance team performance and that certain types of metacognition in cooperation are important for positive teamwork.

A team cognition model derived from an analysis of reflection on cooperation

Teams and teamwork are indispensable, especially when tackling difficult and complex tasks that cannot be easily addressed by a single individual. Because breakdowns in team cooperation can cause accidents, much research attention has been devoted to studies on team cooperation and many teamwork models and theories have been proposed. These models and theories are concerned with observable team behaviors like closed-loop communication, backup-behaviors, and a few traits demonstrating good leadership; however, they do not provide a clear explanation for the mechanism behind them. To better understand team cooperation, it is believed to be additionally necessary to clarify the cognitive factors behind team behaviors. This study aims to examine the factors of cognition underlying cooperation and to propose a team cognition model that can describe and explain these factors in team cooperation. As a method to examine the underlying cognitive factors for cooperation, we analyzed participants’ reflection on cooperation and elicited several important factors for cooperation. Then, based on these factors and the findings of both previous studies by team researchers and human cognitive abilities, a team cognition model that can capture a part of the cognitive factors for team cooperation was developed. Suggestive evidence for the importance of metacognition on cooperation was also provided.

An exploratory study: a measure of workload associated with teamwork

Team workload, which is usually described as an index of the ratio of available team resources to task demands, is believed to be critical for optimal human–computer integration. Although research conceptualizing team workload suggests that the measurement of team workload should consider workload unique to the team, the sum/min/max of members’ workload associated with taskwork referring to individual task performance is often used as an indicator of team workload. In order to better assess workload in team performance in which more than two individuals cooperate and conduct a task, it is also necessary to assess members’ workload associated with teamwork that refers to interpersonal interactions among individuals. The present study aims to develop a measure of workload associated with teamwork and discuss its contribution to operationalizing team workload. Results of team experiments indicate that the Teamwork Workload Scale is able to assess workload associated with teamwork and that it is necessary to assess both workload associated with taskwork and teamwork in order to better assess workload in team performance and operationalize team workload. In order to operationalize and measure team workload, it is necessary to investigate workload in team performance using quantitative data.