Possessing a sufficient level of situation awareness is essential for effective decision making in dynamic environments. In video games, this includes being aware to some extent of the intentions of the opponents. Such high-level awareness hinges upon inferences over the lower-level situation awareness provided by the game state. Traditional plan recognizers are completely passive processes that leave all the initiative to the observed agent. In a situation where the opponent's intentions are unclear, the observer is forced to wait until further observations of the opponent's actions are made to disambiguate the pending goal hypotheses. With the plan recognizer we propose, in contrast, the observer would take the initiative and provoke the opponent, with the expectation that his reaction will give cues as to what his true intentions actually are.

Forces involved in modern conflicts may be exposed to a variety of threats, including coordinated raids of advanced ballistic and cruise missiles. To respond to these, a defending force will rely on a set of combat resources. Determining an efficient allocation and coordinated use of these resources, particularly in the case of multiple simultaneous attacks, is a very complex decision-making process in which a huge amount of data must be dealt with under uncertainty and time pressure. This article presents CORALS (COmbat Resource ALlocation Support), a real-time planner developed to support the command team of a naval force defending against multiple simultaneous threats. In response to such multiple threats, CORALS uses a local planner to generate a set of local plans, one for each threat considered apart, and then combines and coordinates them into a single optimized, conflict-free global plan. The coordination is performed through an iterative process of plan merging and conflict detection and resolution, which acts as a plan repair mechanism. Such an incremental plan repair approach also allows adapting previously generated plans to account for dynamic changes in the tactical situation.

This paper discusses the application of holonic control paradigm to sensor management in military surveillance operations. Sensor management is described both as part of the data fusion process and as a control problem. The choice of holonic control as the most adequate architecture for sensor management in the military environment is explained and its application to surveillance operations illustrated. Holonic control is then simulated using a littoral surveillance scenario to test sensor management with and without feedback from high-level fusion (closed-loop versus open-loop). The results show that closed-loop sensor management significantly enhances global surveillance performance, reduces detection time of threatening objects, and reduces platforms' load, thus increasing stealth and decreasing detectability.

The paper addresses the problem of target-tracking in tactical military surveillance operations. More specifically, a closed-loop approach to adapt the sensing and tracking operations is proposed and compared to the conventional open-loop and static approach. The objective is to control and maintain, over a certain volume of interest and by way of clustering and scheduling strategies, the level of discrimination power required by the mission objectives. The control strategy is based on two cascade loops. The outer loop uses clustering techniques to characterize the volume of interest in terms of discrimination power. This high level information is exploited by the inner loop to compute optimal track update frequency and sensor scheduling strategy.

In military Command & Control applications, the information quality requirements are very context-dependent and seldom predefined. This leaves much room for adaptation. In this paper, the duration of the search & lock-on operations of the fire control radar is estimated and used as an adaptation trigger. The proposed estimation process aims at establishing a quantitative relationship between the quality of the tactical picture and the reaction time available for decision-making. Based on the target’s time of flight, the defensive weapon properties, and the desired range of interception, admissible operational conditions and constraints for the fire control radar are derived to allow the weapon system to achieve its planned interception. These conditions and constraints are re-expressed in terms of tracking quality requirements. Then, adaptation mechanisms are used to select and tune the tracking algorithms and/or manage sensors in order to meet those requirements.