Abstract

Abstract. Human performance can seriously degrade under demanding tasks. To improve performance, agents can reason about the current state of the human, and give the most appropriate and effective support. To enable this, the agent needs a model of a specific person's functional state and performance, which should be valid, as the agent might otherwise give inappropriate advice and even worsen performance. This paper concerns the adaptation of the parameters of the existing functional state model to the individual and validation of the resulting model. First, human experiments have been designed and conducted, whereby measurements related to the model have been performed. Next, this data has been used to obtain appropriate parameter settings for the model, describing the specific subject. Finally, the model, with the tailored parameter settings, has been used to predict human behavior to investigate predictive capabilities of the model. The results have been analyzed using formal verification.

Abstract

413 Int. J. Model. Simul. Sci. Comput. 2011.02:413-443. Downloaded from www.worldscientific.com by UNIVERSITY OF QUEENSLAND on 08/16/15. For personal use only. 414 T. Bosse et al. model. By the parameter estimation, a set of parameter values has been identified by which an adequate representation of a person's functional state when performing a task is achieved.

Abstract. Human task performance varies depending on the task, environment, and states of the human over time. To ensure high effectiveness and efficiency in the execution of complex tasks, adaptive automated assistance of the human may be required. In this paper, a generic design for a multi-agent system architecture is presented and a personal assistant agent is presented that makes use of the proposed architecture. The agent constantly monitors the task execution and well-being of the human via non-intrusive sensors, and intervenes when a problem is detected. A human is given a complex task, while the future performance is predicted using observations and a dynamical model for the human's work pressure and exhaustion. If the predicted exhaustion becomes too high, the ambient agent can assist the human in a number of ways. Experiments show that the support system increases performance with around 13%, and that it enhances the feeling of control of the situation.

Abstract. Human task performance may vary depending on the characteristics of the human, the task and the environment over time. To ensure high effectiveness and efficiency of the execution of tasks, automated personal assistance may be provided to task performers. A personal assistant agent may constantly monitor the human's state and task execution, analyse the state of the human and task, and intervene when a problem is detected. This paper proposes a generic design for a Personal Assistant agent model which can be deployed in a variety of domains. Application of the Personal Assistant model is illustrated by a case study from the naval domain.

Abstract. In this paper a system for visual attention manipulation is introduced and formally described. This system is part of the design of a software agent that supports naval crew in her task to compile a tactical picture of the situation in the field. A case study is described in which the system is used to manipulate a human subject's attention. To this end the system includes a Theory of Mind about human attention and uses this to estimate the subject's current attention, and to determine how features of displayed objects have to be adjusted to make the attention shift in a desired direction. Manipulation of attention is done by adjusting illumination according to the calculated difference between a model describing the subject's attention and a model prescribing it.

Abstract. In this paper, an integrated agent model is introduced addressing mutually interacting Situation Awareness and Functional State dynamics in decision making. This shows how a human's functional state, more specific a human's exhaustion and power, can influence a human's situation awareness, and in turn the decision making. The model is illustrated by a number of simulation scenarios.