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 effects of actions and the initial state of the world. This allows programs to reason about the state of the world and consider the effects of various possible courses of action before committing to a particular behavior. The net effect is that programs may be written at a much higher level of abstraction than is usually possible. The language appears well suited for applications in high level control of robots and industrial processes, intelligent software agents, discrete event simulation, etc. It is based on a formal theory of action specified in an extended version of the situation calculus. A prototype implementation in Prolog has been developed.

We represent properties of actions in a logic programming language that uses both classical negation and negation as failure. The method is applicable to temporal projection problems with incomplete information, as well as to reasoning about the past. It is proved to be sound relative to a semantics of action based on states and transition functions. 1 Introduction This paper extends the work of Eshghi and Kowalski [6], Evans [7] and Apt and Bezem [1] on representing properties of actions in logic programming languages with negation as failure. Our goal is to overcome some of the limitations of the earlier work. The existing formalizations of action in logic programming are adequate for only the simplest kind of temporal reasoning---"temporal projection." In a temporal projection problem, we are given a description of the initial state of the world, and use properties of actions to determine what the world will look like after a series of actions is performed. Moreover, the existing ...

We pursue the perspective of Reiter that in the situation calculus one can formalize primitive, determinate actions with axioms which, among others, include two disjoint sets: a set of successor state axioms and a set of action precondition axioms. We posed ourselves the problem of automatically generating successor state axioms, given only a set of effect axioms and a set of state constraints. This is a special version of what has been traditionally called the ramification problem. To our surprise, we found that there are state constraints whose role is not to yield indirect effects of actions. Rather, they are implicit axioms about action preconditions. As such, they are intimately related to the classical qualification problem. We also discovered that other kinds of state constraints arise; these are related to the formalization of strategic or control information. This paper is devoted to describing our results along these lines, focusing on ramification and qualification state con...

We present a representation of events and action based on interval temporal logic that is significantly more expressive and more natural than most previous AI approaches. The representation is motivated by work in natural language semantics and discourse, temporal logic, and AI planning and plan recognition. The formal basis of the representation is presented in detail, from the axiomatization of time periods to the relationship between actions and events and their effects. The power of the representation is illustrated by applying it to the axiomatization and solution of several standard problems from the AI literature on action and change. An approach to the frame problem based on explanation closure is shown to be both powerful and natural when combined with our representational framework. We also discuss features of the logic that are beyond the scope of many traditional representations, and describe our approach to difficult problems such as external events and simultaneous action...

In recent work we showed that planning problems can be efficiently solved by general propositional satisfiability algorithms (Kautz and Selman 1996). A key issue in this approach is the development of practical reductions of planning to SAT. We introduce a series of different SAT encodings for STRIPS-style planning, which are sound and complete representations of the original STRIPS specification, and relate our encodings to the Graphplan system of Blum and Furst (1995). We analyze the size complexity of the various encodings, both in terms of number of variables and total length of the resulting formulas. This paper complements the empirical evaluation of several of the encodings reported in Kautz and Selman (1996). We also introduce a novel encoding based on the theory of causal planning, that exploits the notionof "lifting" from the theorem-proving community. This new encoding strictly dominates the others in terms of asymptotic complexity. Finally, we consider further reductions i...

Inspired by game theory representations, Bayesian networks, influence diagrams, structured Markov decision process models, logic programming, and work in dynamical systems, the independent choice logic (ICL) is a semantic framework that allows for independent choices (made by various agents, including nature) and a logic program that gives the consequence of choices. This representation can be used as a specification for agents that act in a world, make observations of that world and have memory, as well as a modelling tool for dynamic environments with uncertainty. The rules specify the consequences of an action, what can be sensed and the utility of outcomes. This paper presents a possible-worlds semantics for ICL, and shows how to embed influence diagrams, structured Markov decision processes, and both the strategic (normal) form and extensive (game-tree) form of games within the Thanks to Craig Boutilier and Holger Hoos for detailed comments on this paper. This work was supporte...

A fundamental problem in Knowledge Representation is the design of a logical language to express theories about actions and change. One of the most prominent proposals for such a language is John McCarthy's situation calculus, a formalism which views situations as branching towards the future. The situation calculus has been criticized for imposing severe representational limitations. For example, actions cannot be concurrent, properties change discretely, etc. In this thesis we show that many of these limitations can be overcome. Our work builds upon the discrete situation calculus and on Reiter's monotonic solution to the frame problem. A limitation of Reiter's approach is that it does not allow for state constraints. However, Lin and Reiter have made progress by providing a correctness criterion by which one can determine if an axiomatization can be said to solve the frame problem for theories that include state constraints.

inverse problem of plan recognition has focused on specific kinds of recognition in specific domains. This includes work on story understanding [Bruce 1981, Schank 1975, Wilensky

In the situation calculus, it is sometimes necessary to prove that certain properties are true in all world states accessible from the initial state. This is the case for some forms of reasoning about the physical world, for certain planning applications, and for verifying integrity constraints in databases. Not surprisingly, this requires a suitable form of mathematical induction. This paper motivates the need for proving properties of states in the situation calculus, proposes appropriate induction principles for this task, and gives examples of their use in databases and for reasoning about the physical world. Abbreviated title: Proving Properties of States 1 Introduction The situation calculus [8] is enjoying new popularity these days. One reason is that its expressiveness is considerably richer than has been commonly believed (Gelfond, Lifschitz and Rabinov [2], Pinto and Reiter [10], Schubert [16]). Another is the possibility of precisely characterizing the strengths and limi...

This paper proposes a solution to the frame problem for knowledgeproducing actions. An example of a knowledge-producing action is a sense operation performed by a robot to determine whether or not there is an object of a particular shape within its grasp. The work is an extension of Reiter's solution to the frame problem for ordinary actions and Moore's work on knowledge and action.