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189
Modeling Agents as Qualitative Decision Makers
 Artificial Intelligence
, 1997
"... We investigate the semantic foundations of a method for modeling agents as entities with a mental state which was suggested by McCarthy and by Newell. Our goals are to formalize this modeling approach and its semantics, to understand the theoretical and practical issues that it raises, and to addres ..."
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Cited by 53 (0 self)
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We investigate the semantic foundations of a method for modeling agents as entities with a mental state which was suggested by McCarthy and by Newell. Our goals are to formalize this modeling approach and its semantics, to understand the theoretical and practical issues that it raises, and to address some of them. In particular, this requires specifying the model's parameters and how these parameters are to be assigned (i.e., their grounding). We propose a basic model in which the agent is viewed as a qualitative decision maker with beliefs, preferences, and decision strategy; and we show how these components would determine the agent's behavior. We ground this model in the agent's interaction with the world, namely, in its actions. This is done by viewing model construction as a constraint satisfaction problem in which we search for a model consistent with the agent's behavior and with our general background knowledge. In addition, we investigate the conditions under which a mental st...
The Design Space of Frame Knowledge Representation Systems
 SRI International Artificial Intelligence
, 1993
"... In the past 20 years, AI researchers in knowledge representation (KR) have implemented over 50 frame knowledge representation systems (FRSs). KR researchers have explored a large space of alternative FRS designs. This paper surveys the FRS design space in search of design principles for FRSs. The FR ..."
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Cited by 49 (8 self)
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In the past 20 years, AI researchers in knowledge representation (KR) have implemented over 50 frame knowledge representation systems (FRSs). KR researchers have explored a large space of alternative FRS designs. This paper surveys the FRS design space in search of design principles for FRSs. The FRS design space is defined by the set of alternative features and capabilities  such as the representational constructs  that an FRS designer might choose to include in a particular FRS, as well as the alternative implementations that might exist for a particular feature. The paper surveys the architectural variations explored by different system designers for the frame, the slot, the knowledge base, for accessoriented programming, and for objectoriented programming. We find that few design principles exist to guide an FRS designer as to how particular design decisions will affect qualities of the resulting FRS, such as its worstcase and averagecase theoretical complexity, its actual...
On the Complexity of Conditional Logics
 In Principles of Knowledge Representation and Reasoning: Proc. Fourth International Conference (KR '94
, 1994
"... Conditional logics, introduced by Lewis and Stalnaker, have been utilized in artificial intelligence to capture a broad range of phenomena. In this paper we examine the complexity of several variants discussed in the literature. We show that, in general, deciding satisfiability is PSPACEcomplete fo ..."
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Cited by 39 (7 self)
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Conditional logics, introduced by Lewis and Stalnaker, have been utilized in artificial intelligence to capture a broad range of phenomena. In this paper we examine the complexity of several variants discussed in the literature. We show that, in general, deciding satisfiability is PSPACEcomplete for formulas with arbitrary conditional nesting and NPcomplete for formulas with bounded nesting of conditionals. However, we provide several exceptions to this rule. Of particular note are results showing that (a) when assuming uniformity (i.e., that all worlds agree on what worlds are possible), the decision problem becomes EXPTIMEcomplete even for formulas with bounded nesting, and (b) when assuming absoluteness (i.e., that all worlds agree on all conditional statements), the decision problem is NPcomplete for formulas with arbitrary nesting. 1 INTRODUCTION The study of conditional statements of the form "If : : : then : : :" has a long history in philosophy [Sta68, Lew73, Che80, Vel8...
Algernon  A Tractable System for KnowledgeRepresentation
 SIGART BULLETIN
, 1991
"... AccessLimited Logic (ALL) is a theory of knowledge representation which formalizes the access limitations inherent in a network structured knowledgebase. Where a deductive method such as resolution would retrieve all assertions that satisfy a given pattern, an accesslimited logic retrieves ..."
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Cited by 37 (10 self)
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AccessLimited Logic (ALL) is a theory of knowledge representation which formalizes the access limitations inherent in a network structured knowledgebase. Where a deductive method such as resolution would retrieve all assertions that satisfy a given pattern, an accesslimited logic retrieves only those assertions reachable by following an available access path. The time complexity of inference in ALL is a polynomial function of the size of the accessible portion of the knowledgebase, rather than an exponential function of the size of the entire knowledgebase (as in much past work). AccessLimited Logic, though incomplete, still has a well defined semantics and a weakened form of completeness, Socratic Completeness, which guarantees that for any fact which is a logical consequence of the knowledgebase, there is a series of preliminary queries and assumptions after which a query of the fact will succeed. Algernon implements AccessLimited Logic. Algernon is impo...
Logical Bayesian Networks and their relation to other probabilistic logical models
 In Proceedings of 15th International Conference on Inductive Logic Pogramming (ILP05), volume 3625 of Lecture Notes in Artificial Intelligence
, 2005
"... We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its relation to Probabilistic Relational Models and Bayesian Logic Programs. 1 Probabilistic Logical Models Probabilistic logical models are models combining aspects of probability theory with aspects of ..."
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Cited by 31 (10 self)
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We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its relation to Probabilistic Relational Models and Bayesian Logic Programs. 1 Probabilistic Logical Models Probabilistic logical models are models combining aspects of probability theory with aspects of Logic Programming, firstorder logic or relational languages. Recently a variety of languages to describe such models has been introduced. For some languages techniques exist to learn such models from data. Two examples are Probabilistic Relational Models (PRMs) [4] and Bayesian Logic Programs (BLPs) [5]. These two languages are probably the most popular and wellknown in the Relational Data Mining community. We introduce a new language, Logical Bayesian Networks (LBNs) [2], that is strongly related to PRMs and BLPs yet solves some of their problems with respect to knowledge representation (related to expressiveness and intuitiveness). PRMs, BLPs and LBNs all follow the principle of Knowledge Based Model Construction: they offer a language that can be used to specify general probabilistic logical knowledge and they provide a methodology to construct a propositional model based on this knowledge when given a specific
An Overview of Nonmonotonic Reasoning and Logic Programming
 Journal of Logic Programming, Special Issue
, 1993
"... The focus of this paper is nonmonotonic reasoning as it relates to logic programming. I discuss the prehistory of nonmonotonic reasoning starting from approximately 1958. I then review the research that has been accomplished in the areas of circumscription, default theory, modal theories and logic ..."
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Cited by 28 (2 self)
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The focus of this paper is nonmonotonic reasoning as it relates to logic programming. I discuss the prehistory of nonmonotonic reasoning starting from approximately 1958. I then review the research that has been accomplished in the areas of circumscription, default theory, modal theories and logic programming. The overview includes the major results developed including complexity results that are known about the various theories. I then provide a summary which includes an assessment of the field and what must be done to further research in nonmonotonic reasoning and logic programming. 1 Introduction Classical logic has played a major role in computer science. It has been an important tool both for the development of architecture and of software. Logicians have contended that reasoning, as performed by humans, is also amenable to analysis using classical logic. However, workers in the field of artificial 1 This paper is an updated version of an invited Banquet Address, First Interna...
Towards a Theory of AccessLimited Logic for Knowledge Representation
 IN PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON PRINCIPLES OF KNOWLEDGE REPRESENTATION AND REASONING
, 1989
"... One of the fundamental problems in the theory of knowledge representation is the difficulty of achieving both logical coherence and computational tractability. We present steps toward a theory of accesslimited logic, in which access to assertions in the knowledgebase is constrained by semantic netw ..."
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Cited by 25 (9 self)
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One of the fundamental problems in the theory of knowledge representation is the difficulty of achieving both logical coherence and computational tractability. We present steps toward a theory of accesslimited logic, in which access to assertions in the knowledgebase is constrained by semantic network style locality relations. Where a classical deductive method or logic programming language would retrieve all assertions that satisfy a given pattern, an accesslimited logic retrieves all assertions reachable by following an available access path. The complexity of inference is thus independent of the size of the knowledgebase and depends only on its local connectivity. AccessLimited Logic, though incomplete, still has a well defined semantics and a weakened form of completeness (`Socratic Completeness') and is complete in some important special cases.
Practical solution techniques for firstorder mdps
 Artificial Intelligence
"... Many traditional solution approaches to relationally specified decisiontheoretic planning problems (e.g., those stated in the probabilistic planning domain description language, or PPDDL) ground the specification with respect to a specific instantiation of domain objects and apply a solution approa ..."
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Cited by 25 (1 self)
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Many traditional solution approaches to relationally specified decisiontheoretic planning problems (e.g., those stated in the probabilistic planning domain description language, or PPDDL) ground the specification with respect to a specific instantiation of domain objects and apply a solution approach directly to the resulting ground Markov decision process (MDP). Unfortunately, the space and time complexity of these grounded solution approaches are polynomial in the number of domain objects and exponential in the predicate arity and the number of nested quantifiers in the relational problem specification. An alternative to grounding a relational planning problem is to tackle the problem directly at the relational level. In this article, we propose one such approach that translates an expressive subset of the PPDDL representation to a firstorder MDP (FOMDP) specification and then derives a domainindependent policy without grounding at any intermediate step. However, such generality does not come without its own set of challengesâ€”the purpose of this article is to explore practical solution techniques for solving FOMDPs. To demonstrate the applicability of our techniques, we present proofofconcept results of our firstorder approximate linear programming (FOALP) planner on problems from the probabilistic track
Multientity Models
 Machine Intelligence
, 1995
"... In a seminal paper, McCarthy and Hayes (1969) suggested first order logic as a basis for knowledge representation and reasoning about action. They considered, and rejected, a model of interacting automata as being epistemologically inadequate. This chapter suggests multientity models, a framework ..."
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Cited by 23 (6 self)
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In a seminal paper, McCarthy and Hayes (1969) suggested first order logic as a basis for knowledge representation and reasoning about action. They considered, and rejected, a model of interacting automata as being epistemologically inadequate. This chapter suggests multientity models, a framework closely related to the interacting automata of McCarthy and Hayes, as a tool for knowledge representation and reasoning. Multientity models are designed so as to overcome some of the main criticisms of interacting automata. A number of basic issues in multiagent activity are investigated in the framework of these models, illustrating both the expressiveness and the computational tractability of multientity models. 1 Introduction In an extremely influential paper, McCarthy and Hayes (1969) laid the foundations for much of the research carried out since then on knowledge representation and reasoning about action. In that paper, the authors suggested (firstorder) logic as a basic framewor...
Negation and Proof by Contradiction in AccessLimited Logic
 IN PROCEEDINGS OF THE NINTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 1991
"... AccessLimited Logic (ALL) is a language for knowledge representation which formalizes the access limitations inherent in a network structured knowledgebase. Where a deductive method such as resolution would retrieve all assertions that satisfy a given pattern, an accesslimited logic retrieves all ..."
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Cited by 19 (9 self)
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AccessLimited Logic (ALL) is a language for knowledge representation which formalizes the access limitations inherent in a network structured knowledgebase. Where a deductive method such as resolution would retrieve all assertions that satisfy a given pattern, an accesslimited logic retrieves all assertions reachable by following an available access path. In this paper, we extend previous work to include negation, disjunction, and the ability to make assumptions and reason by contradiction. We show that the extended ALL neg remains Socratically Complete (thus guaranteeing that for any fact which is a logical consequence of the knowledgebase, there exists a series of preliminary queries and assumptions after which a query of the fact will succeed) and computationally tractable. We show further that the key factor determining the computational difficulty of finding such a series of preliminary queries and assumptions is the depth of assumption nesting. We thus demonstrate the existenc...