Our interest is in reactive planners that are embedded in the task execution system and handle error situations implicitly. Given a task and a particular state of the environment the system uses decision-theoretic methods to select and execute the action most likely to achieve a state closest to the goal state. This selection is based not only upon what the effects of an action are, but ~lso on the chances that the action will succeed in achieving those effects . Consider for example, the task of picking up some food for feeding a person. A spoon or a fork can be used. When there is uncertainty associated with the food pickup operation, the planner should consider the chance of success when using the spoon or the fork, and make a choice on the basis of this knowledge. The planner described in this paper selects actions based on their expected utility (defined .as the product of the action’s desirability and its probability of success, given the existing state of the domain) in achieving the desirable effects . As this action selection process continues, the goals of the task are achieved and thereafter, maintained.