Michael Thielscher

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In formal systems for reasoning about actions, the ramification problem denotes the problem of handling indirect effects. These effects are not explicitly represented in action specifications but follow from general laws describing dependencies among components of the world state. An adequate treatment of indirect effects requires a suitably weakened(More)
FLUX is a programming method for the design of agents that reason logically about their actions and sensor information in the presence of incomplete knowledge. The core of FLUX is a system of Constraint Handling Rules, which enables agents to maintain an internal model of their environment by which they control their own behavior. The general action(More)
A central aspect of commonsense reasoning is to sensibly revise one’s beliefs about the world in the presence of new information. The AGM postulates for belief revision, augmented by the DP postulates for iterated belief revision, provide generally accepted criteria for the design of operators by which intelligent agents adapt their beliefs incrementally to(More)
A solution to the ramiication problem caused by underlying domain constraints in Strips-like approaches is presented. We introduce the notion of causal relationships which are used in a post-processing step after having applied an action description. Moreover, we show how the information needed for these post-computations can be automatically extracted from(More)