As agents begin to perform complex tasks alongside humans as collaborative teammates, it becomes crucial that the resulting humanmultiagent teams adapt to time-critical domains. In such domains, adjustable autonomy has proven useful by allowing for a dynamic transfer of control of decision making

The TraumAID system is a tool for assisting physicians during the initial definitive management phase of patients with severe injuries. Originally, TraumAID was conceived as a rule-based expert system combined with a planner. After this architecture had been implemented and evaluated, we began to face the issue of how TraumAID could communicate its plans to physicians in order to influence their behavior and have a positive effect on patient outcome. It was hypothesized that a critiquing approach, in which the system is told what actions the user intends to carry out and produces a critique in response to those intentions, might be appropriate. To meet the needs of physicians engaged in managing trauma cases, critiques must be updated and made available rapidly. They must be clear and succinct, containing only relevant information while still including enough justification ...

function dependent on pairs of agent’s decisions. Unlike previous work, agents must both learn the reward function and exploit it on-line, critical properties for a class of physicallymotivated systems, such as mobile wireless networks. This paper introduces algorithms motivated by the Distributed

Time-critical domains, such as emergency management, demand fast decisions from expert users under stress. Our DecisionCentered Visualization (DCV) system supports decision making by integrating domain knowledge and knowledge about human situation awareness for time-critical visualization

which unlike previous approaches provides statistical guarantees that discarded regions are unlikely to contain the object of interest. In the domain of face detection the system yields detection rates comparable to the best previous systems. Used in real-time applications, the detector runs at 15

? This thesis provides a clarification of trust. We present a formalism for trust which provides us with a tool for precise discussion. The formalism is implementable: it can be embedded in an artificial agent, enabling the agent to make trust-based decisions. Its applicability in the domain of Distributed

This review collates and examines critically a theoretically convergent but widely dispersed body of research on the influence of external environments on the functioning of families as contexts of human development. Investigations falling within this expanding domain include studies

In this work we look at extending the work of (Dean et al. 1993) to handle more complicated schedul-ing problems in which the sources of complexity stem not only from large state spaces but from large ac-tion spaces as well. In these problems it is no longer tractable to compute optimal policies for re-stricted state spaces via policy iteration. We, in-stead, borrow from operations research in applying bottleneck-centered scheduling heuristics (Adams et al. 1988). Additionally, our techniques draw from the work of (Drummond and Bresina 1990). Consider the problem of scheduling planes and gates at a busy airport. A stochastic process describes the arrival of planes at-the airport and is affected by uncon-trollable events such as weather. Stochastic processes

In this work we explore the use of deliberation scheduling for allocating computation among competing decision procedures in solving time-critical scheduling problems in stochastic domains. We present a two-level deliberation scheduling solution. At the higher level deliberation scheduling is used

ing the Graphics Database Application Application Domain Graphics System : Flow of Control : Flow of Data Controller Renderer External Signals Application Database Temporal Graphics Database Figure 3: Schematic of the Abstract Database Model The abstract database model, which I introduce here