Richard B. Scherl

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This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and eeects of actions and the initial state of the world. This allows programs to reason about the state of the world and(More)
This paper describes a novel approach to high-level robot programming based on a highly developed logica] theory of action. The user provides a specification of the robot’s basic actions (their preconditions and effects on the environment) as well as of relevant aspects of the environment, in an extended version of the situation calculus. He can then(More)
This article introduces a new way of understanding subjective probability and its generalization to lower and upper prevision. Instead of asking whether a person is willing to pay given prices for given risky payoffs, we ask whether the person believes he can make a lot of money at those prices. If not—if the person is convinced that no strategy for(More)
Most agents can acquire information about their environments as they operate. A good plan for such an agent is one that not only achieves the goal, but is also executable, i.e., ensures that the agent has enough information at every step to know what to do next. In this paper, we present a formal account of what it means for an agent to know how to execute(More)
A general method of automated modal logic theorem proving is discussed and illustrated. This method is based on the sub-stitutional framework for the development of systems for hybrid reasoning. Sentences in modal logic are translated into a constraint logic in which the constraints represent the connections between worlds in the possible world semantics(More)
This paper describes a novel approach to high-level agent programming based on a highly developed logical theory of action. The user provides a specification of the agents’ basic actions (preconditions and effects) as well as of relevant aspects of the environment, in an extended version of the situation calculus. He can then specify behaviors for the(More)
The goal of our approach to textual inference is to answer queries about events and dates reported in texts; queries that demand inferencing with the relevant background knowledge. Our primary knowledge representation language is AnsProlog. The core inference engine is a combination of AnsProlog and Constraint Logic programming. AnsProlog is particularly(More)
Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent’s state of knowledge. In this paper, we investigate “what sensing actions tell us”, i.e., what an agent comes to know indirectly from the outcome of a sensing action, given knowledge of its actions and state constraints that hold(More)