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  1. Intention is choice with commitment.Philip R. Cohen & Hector J. Levesque - 1990 - Artificial Intelligence 42 (2-3):213-261.
    This paper explores principles governing the rational balance among an agent's beliefs, goals, actions, and intentions. Such principles provide specifications for artificial agents, and approximate a theory of human action (as philosophers use the term). By making explicit the conditions under which an agent can drop his goals, i.e., by specifying how the agent is committed to his goals, the formalism captures a number of important properties of intention. Specifically, the formalism provides analyses for Bratman's three characteristic functional roles played (...)
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  • Qualitative process theory.Kenneth D. Forbus - 1984 - Artificial Intelligence 24 (1-3):85-168.
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  • Nonmonotonic logic and temporal projection.Steve Hanks & Drew McDermott - 1987 - Artificial Intelligence 33 (3):379-412.
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  • Towards a general theory of action and time.James F. Allen - 1984 - Artificial Intelligence 23 (2):123-154.
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  • Temporal constraint networks.Rina Dechter, Itay Meiri & Judea Pearl - 1991 - Artificial Intelligence 49 (1-3):61-95.
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  • Hybrid languages.Patrick Blackburn & Jerry Seligman - 1995 - Journal of Logic, Language and Information 4 (3):251-272.
    Hybrid languages have both modal and first-order characteristics: a Kripke semantics, and explicit variable binding apparatus. This paper motivates the development of hybrid languages, sketches their history, and examines the expressive power of three hybrid binders. We show that all three binders give rise to languages strictly weaker than the corresponding first-order language, that full first-order expressivity can be gained by adding the universal modality, and that all three binders can force the existence of infinite models and have undecidable satisfiability (...)
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  • ``Defeasible Reasoning with Variable Degrees of Justification".John L. Pollock - 2001 - Artificial Intelligence 133 (1-2):233-282.
    The question addressed in this paper is how the degree of justification of a belief is determined. A conclusion may be supported by several different arguments, the arguments typically being defeasible, and there may also be arguments of varying strengths for defeaters for some of the supporting arguments. What is sought is a way of computing the “on sum” degree of justification of a conclusion in terms of the degrees of justification of all relevant premises and the strengths of all (...)
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  • Planning routes through uncertain territory.Drew McDermott & Ernest Davis - 1984 - Artificial Intelligence 22 (2):107-156.
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  • Temporal data base management.Thomas L. Dean & Drew V. McDermott - 1987 - Artificial Intelligence 32 (1):1-55.
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  • Commonsense reasoning about causality: Deriving behavior from structure.Benjamin Kuipers - 1984 - Artificial Intelligence 24 (1-3):169-203.
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  • Towards a theory of intention revision.Wiebe van der Hoek, Wojciech Jamroga & Michael Wooldridge - 2007 - Synthese 155 (2):265-290.
    Although the change of beliefs in the face of new information has been widely studied with some success, the revision of other mental states has received little attention from the theoretical perspective. In particular, intentions are widely recognised as being a key attitude for rational agents, and while several formal theories of intention have been proposed in the literature, the logic of intention revision has been hardly considered. There are several reasons for this: perhaps most importantly, intentions are very closely (...)
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  • (1 other version)Vision, knowledge, and the mystery link.John L. Pollock & Iris Oved - 2005 - Noûs 39 (1):309-351.
    Imagine yourself sitting on your front porch, sipping your morning coffee and admiring the scene before you. You see trees, houses, people, automobiles; you see a cat running across the road, and a bee buzzing among the flowers. You see that the flowers are yellow, and blowing in the wind. You see that the people are moving about, many of them on bicycles. You see that the houses are painted different colors, mostly earth tones, and most are one-story but a (...)
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  • O-Plan: The open planning architecture.Ken Currie & Austin Tate - 1991 - Artificial Intelligence 52 (1):49-86.
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  • The Case for Psychologism in Default and Inheritance Reasoning.Francis Jeffry Pelletier & Renée Elio - 2005 - Synthese 146 (1-2):7-35.
    Default reasoning occurs whenever the truth of the evidence available to the reasoner does not guarantee the truth of the conclusion being drawn. Despite this, one is entitled to draw the conclusion “by default” on the grounds that we have no information which would make us doubt that the inference should be drawn. It is the type of conclusion we draw in the ordinary world and ordinary situations in which we find ourselves. Formally speaking, ‘nonmonotonic reasoning’ refers to argumentation in (...)
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  • A syntactic theory of belief and action.Andrew R. Haas - 1986 - Artificial Intelligence 28 (3):245-292.
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  • Domain-independent planning Representation and plan generation.David E. Wilkins - 1984 - Artificial Intelligence 22 (3):269-301.
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  • Nonmonotonic Reasoning and Causation.Yoav Shoham - 1990 - Cognitive Science 14 (2):213-252.
    It is suggested that taking into account considerations that traditionally fall within the scope of computer science in general, and artificial intelligence in particular, sheds new light on the subject of causation. It is argued that adopting causal notions con be viewed as filling a computational need: They allow reasoning with incomplete information, facilitate economical representations, and afford relatively efficient methods for reasoning about those representations. Specifically, it is proposed that causal reasoning is intimately bound to nonmonotonic reasoning. An account (...)
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  • Temporal logics in AI: Semantical and ontological considerations.Yoav Shoham - 1987 - Artificial Intelligence 33 (1):89-104.
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  • Temporal logic.Antony Galton - 2008 - Stanford Encyclopedia of Philosophy.
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  • Chronological ignorance: Experiments in nonmonotonic temporal reasoning.Yoav Shoham - 1988 - Artificial Intelligence 36 (3):279-331.
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  • How does a box work? A study in the qualitative dynamics of solid objects.Ernest Davis - 2011 - Artificial Intelligence 175 (1):299-345.
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  • Tense Logic and Ontology of Time.Avril Styrman - 2021 - Emilio M. Sanfilippo Et Al, Eds., Proceedings of FOUST 2021: 5th Workshop on Foundational Ontology, Held at JOWO 2021: Episode VII The Bolzano Summer of Knowledge, September 11–18, 2021, Bolzano, Italy, CEURWS, Vol. 2969, 2021.
    This work aims to make tense logic a more robust tool for ontologists, philosophers, knowledge engineers and programmers by outlining a fusion of tense logic and ontology of time. In order to make tense logic better understandable, the central formal primitives of standard tense logic are derived as theorems from an informal and intuitive ontology of time. In order to make formulation of temporal propositions easier, temporal operators that were introduced by Georg Henrik von Wright are developed, and mapped to (...)
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  • The substitutional framework for sorted deduction: Fundamental results on hybrid reasoning.Alan M. Frisch - 1991 - Artificial Intelligence 49 (1-3):161-198.
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  • Modeling a dynamic and uncertain world I.Steve Hanks & Drew McDermott - 1994 - Artificial Intelligence 66 (1):1-55.
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  • A logic of intentions and beliefs.Munindar P. Singh & Nicholas M. Asher - 1993 - Journal of Philosophical Logic 22 (5):513 - 544.
    Intentions are an important concept in Artificial Intelligence and Cognitive Science. We present a formal theory of intentions and beliefs based on Discourse Representation Theory that captures many of their important logical properties. Unlike possible worlds approaches, this theory does not assume that agents are perfect reasoners, and gives a realistic view of their internal architecture; unlike most representational approaches, it has an objective semantics, and does not rely on an ad hoc labeling of the internal states of agents. We (...)
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  • Efficient reasoning about rich temporal domains.Yoav Shoham - 1988 - Journal of Philosophical Logic 17 (4):443 - 474.
    We identify two pragmatic problems in temporal reasoning, the qualification problem and the extended prediction problem, the latter subsuming the infamous frame problem. Solutions to those seem to call for nonmonotonic inferences, and yet naive use of standard nonmonotonic logics turns out to be inappropriate. Looking for an alternative, we first propose a uniform approach to constructing and understanding nonmonotonic logics. This framework subsumes many existing nonmonotonic formalisms, and yet is remarkably simple, adding almost no extra baggage to traditional logic. (...)
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  • Logical Theories of Intention and the Database Perspective.Yoav Shoham - 2009 - Journal of Philosophical Logic 38 (6):633-647.
    While logical theories of information attitudes, such as knowledge, certainty and belief, have flourished in the past two decades, formalization of other facets of rational behavior have lagged behind significantly. One intriguing line of research concerns the concept of intention. I will discuss one approach to tackling the notion within a logical framework, based on a database perspective.
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  • Operators vs. Arguments: The Ins and Outs of Reification.Antony Galton - 2006 - Synthese 150 (3):415-441.
    So-called ‘reified temporal logics’ were introduced by researchers in Artificial Intelligence (AI) in the early 1980s, and gave rise to a long-running series of debates concerning the proper way to represent states, events, causation, action, and other notions identified as crucial to the knowledge representation needs of AI. These debates never resulted in a definitive resolution of the issues under discussion, and indeed continue to produce aftershocks to the present day; none the less, we are now sufficiently far removed in (...)
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  • Event, state, and process in arrow logic.Satoshi Tojo - 1999 - Minds and Machines 9 (1):81-103.
    Artificial agents, which are embedded in a virtual world, need to interpret a sequence of commands given to them adequately, considering the temporal structure for each command. In this paper, we start with the semantics of natural language and classify the temporal structures of various eventualities into such aspectual classes as action, process, and event. In order to formalize these temporal structures, we adopt Arrow Logic. This logic specifies the domain for the valuation of a sentence as an arrow. We (...)
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  • A unifying semantics for time and events.Brandon Bennett & Antony P. Galton - 2004 - Artificial Intelligence 153 (1-2):13-48.
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  • Point algebras for temporal reasoning: Algorithms and complexity.Mathias Broxvall & Peter Jonsson - 2003 - Artificial Intelligence 149 (2):179-220.
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  • A geometric approach to error detection and recovery for robot motion planning with uncertainty.Bruce R. Donald - 1988 - Artificial Intelligence 37 (1-3):223-271.
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  • The topology of boundaries.Margaret M. Fleck - 1996 - Artificial Intelligence 80 (1):1-27.
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  • Processing disjunctions in temporal constraint networks.Eddie Schwalb & Rina Dechter - 1997 - Artificial Intelligence 93 (1-2):29-61.
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  • The token reification approach to temporal reasoning.Lluís Vila & Han Reichgelt - 1996 - Artificial Intelligence 83 (1):59-74.
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  • Default reasoning about spatial occupancy.Murray Shanahan - 1995 - Artificial Intelligence 74 (1):147-163.
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  • Robotlar ve planlama.Varol Akman & Erkan Tin - 1993 - Elektrik Mühendisliği 391:37-43.
    Planlama --- bir amaca ulaşmak üzere bir aksiyonlar bütünü tasarlamak --- yapay zekadaki en temel problemlerden biridir. Bu yazıda, robotikte planlama konusuna mantıkçı (logicist) yaklaşım ele alınmaktadır. [Planning --- devising a plan of action to reach a given goal --- is a fundamental problem in AI. This paper reviews the logicist approach to planning in robotics.].
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  • Order-sorted logic programming with predicate hierarchy.Ken Kaneiwa - 2004 - Artificial Intelligence 158 (2):155-188.
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  • A framework for knowledge-based temporal abstraction.Yuval Shahar - 1997 - Artificial Intelligence 90 (1-2):79-133.
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  • The roles of associational and causal reasoning in problem solving.Reid G. Simmons - 1992 - Artificial Intelligence 53 (2-3):159-207.
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  • Motivated action theory: a formal theory of causal reasoning.Lynn Andrea Stein & Leora Morgenstern - 1994 - Artificial Intelligence 71 (1):1-42.
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  • Aristotelian Roots of Contemporary Tense Logic.Živilė Pabijutaitė & Pranciškus Gricius - forthcoming - Studia Universitatis Babeş-Bolyai Philosophia:65-78.
    Tense logic is a branch of contemporary logic which includes formal devices that allow us to deal with the temporal relations between propositions. The aim of our paper is threefold: 1) to reveal how Aristotelian philosophical ideas about time, truth, possibility and necessity were reinterpreted by the founder of contemporay tense logic Arthur Prior; 2) to discuss what novel solutions to the classical problem of future contingents are available using Priorean invention; 3) to describe how the tools of tense logic (...)
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  • The Meaning and Interpretations of the Japanese Aspect Marker -te-i-.Nishiyama Atsuko - 2006 - Journal of Semantics 23 (2):185-216.
    The Japanese marker _-te-i-_ can have progressive, resultative, and existential perfect readings and has often been regarded as ambiguous. This paper shows that there is no clear evidence that _-te-i-_ is ambiguous. It proposes a monosemous analysis of _-te-i-_ that unifies its multiple readings and shows how progressives and perfects can form a natural semantic class. Within the context of a Discourse Representation Theory, I propose that _-te-i-_ consists of an imperfective operator _-te-_ and a stativizer _-i-_. The imperfective operator (...)
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  • Knowledge and communication: A first-order theory.Ernest Davis - 2005 - Artificial Intelligence 166 (1-2):81-139.
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  • A comparison of point-based approaches to qualitative temporal reasoning.James Delgrande, Arvind Gupta & Tim Van Allen - 2001 - Artificial Intelligence 131 (1-2):135-170.
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  • A critical examination of Allen's theory of action and time.Antony Galton - 1990 - Artificial Intelligence 42 (2-3):159-188.
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  • Problems in formal temporal reasoning.Yoav Shoham & Drew McDermott - 1988 - Artificial Intelligence 36 (1):49-61.
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  • Some considerations on non-linear time intervals.El?Bieta Hajnicz - 1995 - Journal of Logic, Language and Information 4 (4):335-357.
    Most of the descriptions of interval time structures in the first order predicate calculus are based on linear time. However, in the case of intervals, abandoning the condition oflinearity (e.g.LIN in van Benthem's systems) is not sufficient. In this paper, some properties of non-linear time structures are discussed. The most important one is the characterization of location of intervals in a fork of branches. This is connected with the fact that an interval can contain non-collinear subintervals. As a result of (...)
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  • Learning to plan in continuous domains.Gerald F. DeJong - 1994 - Artificial Intelligence 65 (1):71-141.
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  • Intention as commitment toward time.Marc van Zee, Dragan Doder, Leendert van der Torre, Mehdi Dastani, Thomas Icard & Eric Pacuit - 2020 - Artificial Intelligence 283 (C):103270.
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