A unifying action calculus

McCarthy's Situation Calculus is arguably the oldest special-purpose knowledge representation formalism, designed to axiomatize knowledge of actions and their effects. Four decades of research in this area have led to a variety of alternative formalisms: While some approaches can be considered instances or extensions of the classical Situation Calculus, like Reiter's successor state axioms or the Fluent Calculus, there are also special planning languages like ADL and approaches based on a linear (rather than branching) time structure like the Event Calculus. The co-existence of many different calculi has two main disadvantages: The formal relations among them is a largely open issue, and a lot of today's research concerns the transfer of specific results from one approach to another. In this paper, we present a unifying action calculus, which encompasses (well-defined classes of) all of the aforementioned formalisms. Our calculus not only facilitates comparisons and translations between specific approaches, it also allows to solve interesting problems for various calculi at once. We exemplify this by providing a general, calculus-independent solution to a problem of practical relevance, which is intimately related to McCarthy's quest for elaboration tolerant formalisms: the modularity of domain axiomatizations.     

John McCarthy's legacy

This special issue is dedicated to John McCarthy, founding father of Artificial Intelligence. It contains a collection of recent contributions to the field of knowledge representation and reasoning, a field that McCarthy founded and that has been a main focus of his research during the last half century. In this introductory article, we survey some of McCarthy's major contributions to the field of knowledge representation and reasoning, and situate the papers in this special issue in the context of McCarthy's previous work.     

OWL rules: A proposal and prototype implementation

Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present the Semantic Web Rule Language (SWRL), a Horn clause rules extension to OWL that overcomes many of these limitations. SWRL extends OWL in a syntactically and semantically coherent manner: the basic syntax for SWRL rules is an extension of the abstract syntax for OWL DL and OWL Lite; SWRL rules are given formal meaning via an extension of the OWL DL model-theoretic semantics; SWRL rules are given an XML syntax based on the OWL XML presentation syntax; and a mapping from SWRL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. We discuss the expressive power of SWRL, showing that the ontology consistency problem is undecidable, provide several examples of SWRL usage, and discuss a prototype implementation of reasoning support for SWRL.     

A semantic characterization of a useful fragment of the situation calculus with knowledge

The situation calculus, as proposed by McCarthy and Hayes, and developed over the last decade by Reiter and co-workers, is reconsidered. A new logical variant called ES is proposed that captures much of the expressive power of the original, but where certain technical results are much more easily proved. This is illustrated using two existing non-trivial results: the determinacy of knowledge theorem of Reiter and the regression theorem, which reduces reasoning about the future to reasoning about the initial situation. Furthermore, we show the correctness of our approach by embedding ES in Reiter's situation calculus.     

Iterated belief change in the situation calculus

John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.     

Formalising the Fisherman's Folly puzzle

This paper investigates the challenging problem of encoding the common sense knowledge involved in the manipulation of spatial objects from a reasoning about actions and change perspective. In particular, we propose a formal solution to a puzzle composed of non-trivial objects (such as holes and strings) assuming a version of the Situation Calculus written over first-order Equilibrium Logic, whose models generalise the stable model semantics.     

Event calculus and temporal action logics compared

We compare the event calculus and temporal action logics (TAL), two formalisms for reasoning about action and change. We prove that, if the formalisms are restricted to integer time, inertial fluents, and relational fluents, and if TAL action type specifications are restricted to definite reassignment of a single fluent, then the formalisms are not equivalent. We argue that equivalence cannot be restored by using more general TAL action type specifications. We prove however that, if the formalisms are further restricted to single-step actions, then they are logically equivalent.     

Applications of parallel processing technologies in heuristic search planning: methodologies and experiments

The goal of this paper is to investigate the application of parallel programming techniques to boost the performance of heuristic search‐based planning systems in various aspects. It shows that an appropriate parallelization of a sequential planning system often brings gain in performance and/or scalability. We start by describing general schemes for parallelizing the construction of a plan. We then discuss the applications of these techniques to two domain‐independent heuristic search‐based planners—a competitive conformant planner (CP A) and a state‐of‐the‐art classical planner (FF). We present experimental results—on both shared memory and distributed memory platforms—which show that the performance improvements and scalability are obtained in both cases. Finally, we discuss the issues that should be taken into consideration when designing a parallel planning system and relate our work to the existing literature. Copyright © 2009 John Wiley & Sons, Ltd.     

A causal approach to nonmonotonic reasoning

We introduce logical formalisms of production and causal inference relations based on input/output logics of Makinson and Van der Torre [J. Philos. Logic 29 (2000) 383–408]. These inference relations will be assigned, however, both standard semantics (giving interpretation to their rules), and natural nonmonotonic semantics based on the principle of explanation closure. The resulting nonmonotonic formalisms will be shown to provide a logical representation of abductive reasoning, and a complete characterization of causal nonmonotonic reasoning from McCain and Turner [Proc. AAAI-97, Providence, RI, 1997, pp. 460–465]. The results of the study suggest production and causal inference as general nonmonotonic formalisms providing an alternative representation for a significant part of nonmonotonic reasoning.     

Deductive efficiency,belief revision and acting

Abstract

The SNePS inference engine is optimized for deductive efficiency, i.e. all beliefs acquired via inference are added to the agent's beliefs so that future queries may be answered by a retrieval rather than rederivation. An assumption-based truth maintenance system keeps track of the derivation histories of derived beliefs. We show how such an architecture simplifies the ontology of prepositional representations of plans; acts; preconditions, and effects of actions. In addition, the deductive efficiency of the basic system automatically extends itself to efficient search of plans, and hierarchical plan decompositions.     

Object-Action Complexes: Grounded abstractions of sensory-motor processes

This paper formalises Object-Action Complexes (OACs) as a basis for symbolic representations of sensory-motor experience and behaviours. OACs are designed to capture the interaction between objects and associated actions in artificial cognitive systems. This paper gives a formal definition of OACs, provides examples of their use for autonomous cognitive robots, and enumerates a number of critical learning problems in terms of OACs.     

On combinations of propositional dynamic logic and doxastic modal logics

We prove completeness and decidability results for a family of combinations of propositional dynamic logic and unimodal doxastic logics in which the modalities may interact. The kind of interactions we consider include three forms of commuting axioms, namely, axioms similar to the axiom of perfect recall and the axiom of no learning from temporal logic, and a Church–Rosser axiom. We investigate the influence of the substitution rule on the properties of these logics and propose a new semantics for the test operator to avoid unwanted side effects caused by the interaction of the classic test operator with the extra interaction axioms. This paper is a revised and extended version of Schmidt and Tishkovsky (2003).     

HYPOTHETICAL REASONING ABOUT ACTIONS: FROM SITUATION CALCULUS TO EVENT CALCULUS

Hypothetical reasoning about actions is the activity of preevaluating the effect of performing actions in a changing domain; this reasoning underlies applications of knowledge representation, such as planning and explanation generation. Action effects are often specified in the language of situation calculus, introduced by McCarthy and Hayes in 1969. More recently, the event calculus has been defined to describe actual actions, i.e., those that have occurred in the past, and their effects on the domain. Altough the two formalisms share the basic ontology of atomic actions and fluents, situation calculus cannot represent actual actions while event calculus cannot represent hypotethical actions. In this article, the language and the axioms of event calculus are extended to allow representing and reasoning about hypothetical actions, performed either at the present time or in the past, altough counterfactuals are not supported. Both event calculus and its extension are defined as logic programs so that theories are readily adaptable for Prolog query interpretation. For a reasonably large class of theories and queries, Prolog interpretation is shown to be sound and complete w.r.t. the main semantics for logic programs.     

基于动态描述逻辑DDL的动作理论

基于一阶谓词逻辑或高阶逻辑的动作理论与采用命题语言的动作理论之间存在一个关于描述和推理能力的鸿沟;作为描述逻辑的动态扩展,动态描述逻辑DDL为基于描述逻辑的动作刻画和推理提供了一种途径.系统地研究了基于DDL的动作表示和推理问题.首先,在应用描述逻辑对静态领域知识进行刻画的基础上,引入带参数的原子动作定义式和带参数的复...