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...

We introduce a new subclass of Allen's interval algebra we call "ORDHorn subclass," which is a strict superset of the "pointisable subclass." We prove that reasoning in the ORD-Horn subclass is a polynomial-time problem and show that the path-consistency method is sufficient for deciding satisfiability. Further, using an extensive machine-generated case analysis, we show that the ORD-Horn subclass is a maximal tractable subclass of the full algebra (assuming<F NaN> P6=NP). In fact, it is the unique greatest tractable subclass amongst the subclasses that contain all basic relations. This work has been supported by the German Ministry for Research and Technology (BMFT) under grant ITW 8901 8 as part of the WIP project and under grant ITW 9201 as part of the TACOS project. 1 1 Introduction Temporal information is often conveyed qualitatively by specifying the relative positions of time intervals such as ". . . point to the figure while explaining the performance of the system . . . "...

Our focus in this paper is on natural exogenous actions (Pinto [23]), namely those which occur in response to known laws of physics, like a ball bouncing at times determined by Newtonian equations of motion. The property of such actions that we wish to capture is that they must occur at their predicted times, provided no earlier actions (natural or agent initiated) prevent them from occurring. Because several such actions may occur simultaneously, we need a theory of concurrency. Because such actions may be modeled by equations of motion, we need to represent continuous time. This paper shows how to gracefully accommodate all these features within the situation calculus, without sacrificing the simple solution to the frame problem of Reiter [25]. One nice consequence of this approach is a situation calculus specification of deductive planning, with continuous time and true concurrency, and where the agent can incorporate external natural event occurrences into her...

This technical definition will only make sense toe reader by Ch. 4, once goals and management processes have been described. All that matters forrs section is that a difference between goals and perturbance be noted by the reader. Astate perturbance is not a goal, but it arises out of the processing of goals. In Ch. 7, arelation00 perturbance and "emotion" is discussed. 43 . Sloman says of certain moods that they are "persistent states with dispositional power to color and modify a host of other states and processes. Such moodscan39061-6 be caused by cognitive events with semantic content, though they need not be.[...]0-64000 their control function does not require specific semantic content, though theycan0371-62 cognitive processes that do involve semantic content." (Sloman, 1992b Section 6).A 39642 view is taken in (Oatley, 1992). To be more precise, moods are temporary control stateswhich9881-5 the prominence of some motivators while decreasing others. In particular, they affectthe 41330-5 that certain "goal generators" are triggered. Moreover, moods affect the valenceofce 39476 evaluations, and the likelihood of affective evaluations (perhaps by modifying thresholdsofsholds 42 that trigger evaluations). It is not yet clear whether moods as defined here are9531 - or whether they merely emerge as side-effects of functional processes. . A reflex is a ballistic form of behaviour that can be specified by a narrow setw rules based on input integration and a narrow amount of internal state. There aretwo0981 of reflexes: simple reflexes and fixed action patterns. A simple reflex involves oneaction,-43000 a fixed action pattern involves a collection of actions. Usually, at most only asmall-4120 of perceptual feedback influences reflex action. This would require a definit...

A class of interval-based temporal languages for uniformly representing and reasoning about actions and plans is presented. Actions are represented by describing what is true while the action itself is occurring, and plans are constructed by temporally relating actions and world states. The temporal languages are members of the family of Description Logics, which are characterized by high expressivity combined with good computational properties. The subsumption problem for a class of temporal Description Logics is investigated and sound and complete decision procedures are given. The basic language TL-F is considered #rst: it is the composition of a temporal logic TL # able to express interval temporal networks # together with the non-temporal logic F # a Feature Description Logic. It is proven that subsumption in this language is an NP-complete problem. Then it is shown how to reason with the more expressive languages TLU-FU and TL-ALCF . The former adds disjunction both at...

While the worst-case computational properties of Allen's calculus for qualitative temporal reasoning have been analyzed quite extensively, the determination of the empirical efficiency of algorithms for solving the consistency problem in this calculus has received only little research attention. In this paper, we will demonstrate that using the ORD-Horn class in Ladkin and Reinefeld's backtracking algorithm leads to performance improvements when deciding consistency of hard instances in Allen's calculus. For this purpose, we prove that Ladkin and Reinefeld's algorithm is complete when using the ORD-Horn class, we identify phase transition regions of the reasoning problem, and compare the improvements of ORD-Horn with other heuristic methods when applied to instances in the phase transition region. Finally, we give evidence that combining search methods orthogonally can dramatically improve the performance of the backtracking algorithm. Contents 1 Introduction 1 2 Allen's...

This paper introduces a new logical formalism, intended for temporal conceptual modelling, as a natural combination of the well-known description logic DLR and point-based linear temporal logic with Since and Until. We define a query language (where queries are non-recursive Datalog programs and atoms are complex DLR US expressions) and investigate the problem of checking query containment under the constraints defined by DLR US conceptual schemas, as well as the problems of schema satisfiability and logical implication. Although it is shown that reasoning in full DLR US is undecidable, we identify the decidable (in a sense, maximal) fragment DLR - US by allowing applications of temporal operators to formulas and entities only (but not to relation expressions) . We obtain the following hierarchy of complexity results: (a) reasoning in DLR - US with atomic formulas is EXPTIME-complete, (b) satisfiability and logical implication of arbitrary DLR - US formulas is EXPSPACE-complete, and (c) the problem of checking query containment of non-recursive Datalog queries under DLR - US constraints is decidable in 2EXPTIME. 1 1

This paper surveys the temporal extensions of Description Logics appearearing in the literature. The analysis considers a large spectrum of approaches appearearing in the Temporal Description Logics area: from the loosely coupled approaches { which comprise, for example, the enhancement of simple Description Logics with a constraint based mechanism { to the most principled ones { which consider a combined semantics for the abstract and the temporal domains. It will be shown how these latter approaches have a strict connection with temporal logics

A formal language for representing and reasoning about time and action is presented. We employ an action representation in the style of Allen, where an action is represented by describing the time course of events while the action occurs. In this sense, an action is defined by means of temporal constraints on the world states, which pertain to the action itself, and on other more elementary actions occurring over time. A distinction between action types and individual actions is supported by the formalism. Plans are seen as complex actions whose properties possibly change with time. The formal representation language used in this paper is a description logic, and it is provided with a well founded syntax, semantics and calculus. Algorithms for the subsumption and recognition tasks -- forming the basis for action management -- are provided. 1 INTRODUCTION The goal of this work is to investigate a formal framework that permits dealing with time, actions and plans in a...

Although the computational perspective on cognitive tasks has always played a major role in Artificial Intelligence, the interest in the precise determination of the computational costs that are required for solving typical AI problems has grown only recently. In this paper, we will describe what insights a computational complexity analysis can provide and what methods are available to deal with the complexity problem. This work was partially supported by the European Commission as part of DRUMS-II, the ESPRIT Basic Research Project P6156. 1 Introduction It is well-known that typical AI problems, such as natural language understanding, scene interpretation, planning, configuration, or diagnosis are computationally difficult. Hence, it seems to be worthless to analyze the computational complexity of these problems. In fact, some people believe that all AI problems are NP-hard or even undecidable. Conceiving AI as a scientific field that has as its goal the analysis and synthesis of...