Jens Claßen

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Typical Golog programs for robot control are nonterminating. Analyzing such programs so far requires metatheoretic arguments involving complex fix-point constructions. In this paper we propose a logic based on the situation calculus variant ES , which includes elements from branching time, dynamic and process logics and where the meaning of programs is(More)
The action language Golog has been applied successfully to the control of robots, among other things. Perhaps its greatest advantage is that a user can write programs which constrain the search for an executable plan in a flexible manner. However, when general planning is needed, Golog supports this only in principle, but does not measure up with(More)
The Planning Domain Definition Language (PDDL) has become a common language to specify planning problems, facilitating the formulation of benchmarks and a direct comparison of planners. Over the years PDDL has been extended beyond STRIPS and ADL in various directions, for example, by adding time and concurrent actions. The current semantics of PDDL is(More)
The action programming language GOLOG has been found useful for the control of autonomous agents such as mobile robots. In scenarios like these, tasks are often open-ended so that the respective control programs are non-terminating. Before deploying such programs on a robot, it is often desirable to verify that they meet certain requirements. For this(More)
GOLOG is a high-level action programming language for controlling autonomous agents such as mobile robots. It is defined on top of a logic-based action theory expressed in the Situation Calculus. Before a program is deployed onto an actual robot and executed in the physical world, it is desirable, if not crucial, to verify that it meets certain requirements(More)
The Golog family of action languages has proven to be a useful means for the high-level control of autonomous agents, such as mobile robots. In particular, the IndiGolog variant, where programs are executed in an online manner, is applicable in realistic scenarios where agents possess only incomplete knowledge about the state of the world, have to use(More)