Switch to: References

Add citations

You must login to add citations.
  1. Is logicist cognitive science possible?Alan Garnham - 1993 - Mind and Language 8 (1):49-71.
    This paper argues against Oaksford and Chater's claim that logicist cognitive science is not possible. It suggests that there arguments against logicist cognitive science are too closely tied to the account of Pylyshyn and of Fodor, and that the correct way of thinking about logicist cognitive science is in a mental models framework.
    Download  
     
    Export citation  
     
    Bookmark   80 citations  
  • A mathematical treatment of defeasible reasoning and its implementation.Guillermo R. Simari & Ronald P. Loui - 1992 - Artificial Intelligence 53 (2-3):125-157.
    We present a mathematical approach to defeasible reasoning based on arguments. This approach integrates the notion of specificity introduced by Poole and the theory of warrant presented by Pollock. The main contribution of this paper is a precise, well-defined system which exhibits correct behavior when applied to the benchmark examples in the literature. It aims for usability rather than novelty. We prove that an order relation can be introduced among equivalence classes of arguments under the equi-specificity relation. We also prove (...)
    Download  
     
    Export citation  
     
    Bookmark   80 citations  
  • Qualitative probabilities for default reasoning, belief revision, and causal modeling.Moisés Goldszmidt & Judea Pearl - 1996 - Artificial Intelligence 84 (1-2):57-112.
    This paper presents a formalism that combines useful properties of both logic and probabilities. Like logic, the formalism admits qualitative sentences and provides symbolic machinery for deriving deductively closed beliefs and, like probability, it permits us to express if-then rules with different levels of firmness and to retract beliefs in response to changing observations. Rules are interpreted as order-of-magnitude approximations of conditional probabilities which impose constraints over the rankings of worlds. Inferences are supported by a unique priority ordering on rules (...)
    Download  
     
    Export citation  
     
    Bookmark   68 citations  
  • Conditional entailment: Bridging two approaches to default reasoning.Hector Geffner & Judea Pearl - 1992 - Artificial Intelligence 53 (2-3):209-244.
    Download  
     
    Export citation  
     
    Bookmark   49 citations  
  • Defeasible reasoning.Robert C. Koons - 2008 - Stanford Encyclopedia of Philosophy.
    Download  
     
    Export citation  
     
    Bookmark   38 citations  
  • The frame problem.Murray Shanahan - 2008 - Stanford Encyclopedia of Philosophy.
    Download  
     
    Export citation  
     
    Bookmark   39 citations  
  • ``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 (...)
    Download  
     
    Export citation  
     
    Bookmark   44 citations  
  • Nonmonotonic causal theories.Joohyung Lee, Vladimir Lifschitz & Hudson Turner - 2004 - Artificial Intelligence 153 (1-2):49-104.
    cuted actions. It has been applied to several challenge problems in the theory of commonsense knowledge. We study the relationship between this formalism and other work on nonmonotonic reasoning and knowl-.
    Download  
     
    Export citation  
     
    Bookmark   42 citations  
  • Mental models and the tractability of everyday reasoning.Mike Oaksford - 1993 - Behavioral and Brain Sciences 16 (2):360-361.
    Download  
     
    Export citation  
     
    Bookmark   36 citations  
  • From statistical knowledge bases to degrees of belief.Fahiem Bacchus, Adam J. Grove, Joseph Y. Halpern & Daphne Koller - 1996 - Artificial Intelligence 87 (1-2):75-143.
    Download  
     
    Export citation  
     
    Bookmark   33 citations  
  • Probabilistic Horn abduction and Bayesian networks.David Poole - 1993 - Artificial Intelligence 64 (1):81-129.
    Download  
     
    Export citation  
     
    Bookmark   25 citations  
  • Reasoning about action I.Matthew L. Ginsberg & David E. Smith - 1988 - Artificial Intelligence 35 (2):165-195.
    Download  
     
    Export citation  
     
    Bookmark   23 citations  
  • Ramification and causality.Michael Thielscher - 1997 - Artificial Intelligence 89 (1-2):317-364.
    Download  
     
    Export citation  
     
    Bookmark   22 citations  
  • (1 other version)Active logic semantics for a single agent in a static world.Michael L. Anderson, Walid Gomaa, John Grant & Don Perlis - 2008 - Artificial Intelligence 172 (8-9):1045-1063.
    Download  
     
    Export citation  
     
    Bookmark   18 citations  
  • Answer set programming and plan generation.Vladimir Lifschitz - 2002 - Artificial Intelligence 138 (1-2):39-54.
    Download  
     
    Export citation  
     
    Bookmark   20 citations  
  • 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 (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  • Everyday reasoning and logical inference.Jon Barwise - 1993 - Behavioral and Brain Sciences 16 (2):337-338.
    Download  
     
    Export citation  
     
    Bookmark   17 citations  
  • Representing action: indeterminacy and ramifications.Enrico Giunchiglia, G. Neelakantan Kartha & Vladimir Lifschitz - 1997 - Artificial Intelligence 95 (2):409-438.
    Download  
     
    Export citation  
     
    Bookmark   16 citations  
  • Frames in the space of situations.Vladimir Lifschitz - 1990 - Artificial Intelligence 46 (3):365-376.
    Download  
     
    Export citation  
     
    Bookmark   16 citations  
  • Nonmonotonic reasoning in the framework of situation calculus.Andrew B. Baker - 1991 - Artificial Intelligence 49 (1-3):5-23.
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  • Embracing causality in default reasoning.Judea Pearl - 1988 - Artificial Intelligence 35 (2):259-271.
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  • Impediments to universal preference-based default theories.Jon Doyle & Michael P. Wellman - 1991 - Artificial Intelligence 49 (1-3):97-128.
    Download  
     
    Export citation  
     
    Bookmark   12 citations  
  • What is answer set programming?Vladimir Lifschitz - unknown
    Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in knowledge representation, it is particularly useful in knowledge-intensive applications. ASP programs consist of rules that look like Prolog rules, but the computational mechanisms used in ASP are different: they are based on the ideas that have led to the creation of fast satisfiability solvers for propositional logic.
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • A circumscriptive theorem prover.Matthew L. Ginsberg - 1989 - Artificial Intelligence 39 (2):209-230.
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  • The logical content of theories of deduction.Wilfrid Hodges - 1993 - Behavioral and Brain Sciences 16 (2):353-354.
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  • A circumscriptive calculus of events.Murray Shanahan - 1995 - Artificial Intelligence 77 (2):249-284.
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  • Précis of Deduction.Philip N. Johnson-Laird & Ruth M. J. Byrne - 1993 - Behavioral and Brain Sciences 16 (2):323-333.
    How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • How does a box work? A study in the qualitative dynamics of solid objects.Ernest Davis - 2011 - Artificial Intelligence 175 (1):299-345.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • (1 other version)The logical foundations of goal-regression planning in autonomous agents.John L. Pollock - 1998 - Artificial Intelligence 106 (2):267-334.
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • Mid-sized axiomatizations of commonsense problems: A case study in egg cracking.Leora Morgenstern - 2001 - Studia Logica 67 (3):333-384.
    We present an axiomatization of a problem in commonsense reasoning, characterizing the proper procedure for cracking an egg and transferring its contents to a bowl. The axiomatization is mid-sized, larger than toy problems such as the Yale Shooting Problem or the Suitcase Problem, but much smaller than the comprehensive axiomatizations associated with CYC and HPKB. This size of axiomatization permits the development of non-trivial, reusable core theories of commonsense reasoning, acts as a testbed for existing theories of commonsense reasoning, and (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • A unifying action calculus.Michael Thielscher - 2011 - Artificial Intelligence 175 (1):120-141.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Rigor mortis: A response to Nilsson's 'logic and artificial intelligence'.Lawrence Birnbaum - 1991 - Artificial Intelligence 47 (1-3):57-78.
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • Modeling a dynamic and uncertain world I.Steve Hanks & Drew McDermott - 1994 - Artificial Intelligence 66 (1):1-55.
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • Mental models or formal rules?Philip N. Johnson-Laird & Ruth M. J. Byrne - 1993 - Behavioral and Brain Sciences 16 (2):368-380.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • Mental models cannot exclude mental logic and make little sense without it.Martin D. S. Braine - 1993 - Behavioral and Brain Sciences 16 (2):338-339.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • On rules, models and understanding.Jonathan St B. T. Evans - 1993 - Behavioral and Brain Sciences 16 (2):345-346.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • The Dramatic True Story of the Frame Default.Vladimir Lifschitz - 2015 - Journal of Philosophical Logic 44 (2):163-176.
    This is an expository article about the solution to the frame problem proposed in 1980 by Raymond Reiter. For years, his “frame default” remained untested and suspect. But developments in some seemingly unrelated areas of computer science—logic programming and satisfiability solvers—eventually exonerated the frame default and turned it into a basis for important applications.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Deduction and degrees of belief.David Over - 1993 - Behavioral and Brain Sciences 16 (2):361-362.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • The Qualification Problem: A solution to the problem of anomalous models.Michael Thielscher - 2001 - Artificial Intelligence 131 (1-2):1-37.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • Reasoning about action and change.Helmut Prendinger & Gerhard Schurz - 1996 - Journal of Logic, Language and Information 5 (2):209-245.
    Reasoning about change is a central issue in research on human and robot planning. We study an approach to reasoning about action and change in a dynamic logic setting and provide a solution to problems which are related to the Frame problem. Unlike most work on the frame problem the logic described in this paper is monotonic. It (implicitly) allows for the occurrence of actions of multiple agents by introducing non-stationary notions of waiting and test. The need to state a (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • Deductive reasoning: What are taken to be the premises and how are they interpreted?Samuel Fillenbaum - 1993 - Behavioral and Brain Sciences 16 (2):348-349.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • The frame problem, the relevance problem, and a package solution to both.Yingjin Xu & Pei Wang - 2012 - Synthese 187 (S1):43-72.
    As many philosophers agree, the frame problem is concerned with how an agent may efficiently filter out irrelevant information in the process of problem-solving. Hence, how to solve this problem hinges on how to properly handle semantic relevance in cognitive modeling, which is an area of cognitive science that deals with simulating human's cognitive processes in a computerized model. By "semantic relevance", we mean certain inferential relations among acquired beliefs which may facilitate information retrieval and practical reasoning under certain epistemic (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Two counterexamples related to Baker's approach to the frame problem.G. Neelakantan Kartha - 1994 - Artificial Intelligence 69 (1-2):379-391.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Default reasoning about spatial occupancy.Murray Shanahan - 1995 - Artificial Intelligence 74 (1):147-163.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Deduction by children and animals: Does it follow the Johnson-Laird & Byrne model?Hank Davis - 1993 - Behavioral and Brain Sciences 16 (2):344-344.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Mental-model theory and rationality.Pascal Engel - 1993 - Behavioral and Brain Sciences 16 (2):345-345.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • On modes of explanation.Rachel Joffe Falmagne - 1993 - Behavioral and Brain Sciences 16 (2):346-347.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • The argument for mental models is unsound.James H. Fetzer - 1993 - Behavioral and Brain Sciences 16 (2):347-348.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • A number of questions about a question of number.Alan Garnham - 1993 - Behavioral and Brain Sciences 16 (2):350-351.
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Mental models: Rationality, representation and process.D. W. Green - 1993 - Behavioral and Brain Sciences 16 (2):352-353.
    Download  
     
    Export citation  
     
    Bookmark   3 citations