the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI...
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ISBN:
(纸本)9781479986460
the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI agents in our previous work. In order that the BDI agents are more and more suitable for modelling our real world, a BDI agent programming language with fuzzied-belief based on a existing BDI agent programming language is developed in this paper. the new language is more flexible and human-like compared to non-fuzzy based BDI agent language in the real world applications. Particularly, it provides a more reasonable planning selection mechanism. the reasoning capability of the previous BDI language is improved due to the work in this paper.
In spite of the existence of a close relationship between logicprogramming and non-monotonic reasoning, in the past the two research areas have progressed largely independently of each other. Recently, however, a new...
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this paper presents a modified version of forward chaining method of reasoning and a prototype implementation called Sylar - System for logic and automatedreasoning, which can be used for situation management. the me...
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ISBN:
(纸本)9783319198576;9783319198569
this paper presents a modified version of forward chaining method of reasoning and a prototype implementation called Sylar - System for logic and automatedreasoning, which can be used for situation management. the method, presented by the authors, implements Modus Ponens and Modus Tollens by Truth tables and a SAT solver to discover hidden knowledge and suggest decisions. Also, it gives the opportunity to use multi-step inferences. Proposed method is suitable for this specific kind of decision making process.
First-order coherent logic (CL) extends resolution logic in that coherent formulas allow certain existential quantifications. A substantial number of reasoning problems (e.g., in confluence theory, lattice theory and ...
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ISBN:
(纸本)354030553X
First-order coherent logic (CL) extends resolution logic in that coherent formulas allow certain existential quantifications. A substantial number of reasoning problems (e.g., in confluence theory, lattice theory and projective geometry) can be formulated directly in CL without any clausification or Skolemization. CL has a natural proof theory, reasoning is constructive and proof objects can easily be obtained. We prove completeness of the proof theory and give a linear translation from FOL to CL that preserves logical equivalence. these properties make CL well-suited for providing automatedreasoning support to logical frameworks. the proof theory has been implemented in Prolog, generating proof objects that can be verified directly in the proof assistant Coq. the prototype has been tested on the proof of Hessenberg's theorem, which could be automated to a considerable extent. Finally, we compare the prototype to some automatedtheorem provers on selected problems.
the fascination for generating reasons and drawing inferences has given a tremendous impetus to research in theoretical computer science. In spite of having well defined constructs and globally accepted notations for ...
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ISBN:
(纸本)9781479960491
the fascination for generating reasons and drawing inferences has given a tremendous impetus to research in theoretical computer science. In spite of having well defined constructs and globally accepted notations for logic and First-order theorem provers, theorem proving is still a semi-decidable problem having exponential time complexity. On the other hand swarm intelligence is a swiftly growing research area for solving optimization problems. this paper presents a novel approach for automatedtheorem proving using meta-heuristics. In the present research we have tried to combine these two entirely different zones of computer science, i.e. meta-heuristics and concrete logic via modeling theorem provers as an optimization problem in a sound practical manner. Also we have experimentally shown how to automate first order reasoning using Artificial Bee Colony algorithm on a sample problem expressed in First-order predicate calculus.
Modelling, reasoning and verifying complex situations involving a system of agents is crucial in all phases of the development of a number of safety-critical systems. In particular, it is of fundamental importance to ...
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Modelling, reasoning and verifying complex situations involving a system of agents is crucial in all phases of the development of a number of safety-critical systems. In particular, it is of fundamental importance to have tools and techniques to reason about the doxastic and epistemic states of agents, to make sure that the agents behave as intended. In this paper we introduce a computationally grounded logic called COGWED and we present two types of semantics that support a range of practical situations. We provide model checking algorithms, complexity characterisations and a prototype implementation. We validate our proposal against a case study from the avionic domain: we assess and verify the situational awareness of pilots flying an aircraft with several automated components in off-nominal conditions.
Over the last forty years, computer scientists have invented or borrowed numerous logics for reasoning about digital systems. Here, I would like to concentrate on three of them: Linear Time Temporal logic (LTL), branc...
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ISBN:
(纸本)9783319085876;9783319085869
Over the last forty years, computer scientists have invented or borrowed numerous logics for reasoning about digital systems. Here, I would like to concentrate on three of them: Linear Time Temporal logic (LTL), branching time Computation Tree temporal logic (CTL), and Propositional Dynamic logic (PDL), with and without converse. More specifically, I would like to present results and techniques on how to solve the satisfiability problem in these logics, with global assumptions, using the tableau method. the issues that arise are the typical tensions between computational complexity, practicality and scalability. this is joint work with Linh Anh Nguyen, Pietro Abate, Linda Postniece, Florian Widmann and Jimmy thomson.
this paper contributes to the area of inductive logicprogramming by presenting a new learning framework that allows the learning of weak constraints in Answer Set programming (ASP). the framework, called Learning fro...
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this paper contributes to the area of inductive logicprogramming by presenting a new learning framework that allows the learning of weak constraints in Answer Set programming (ASP). the framework, called Learning from Ordered Answer Sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are preferred to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.
A new system CMODELS-2 which is able to fix ASSAT's disadvantages was presented. It was found that the new system organizes the search process more efficiently than ASSAT as it does not explore the same part of th...
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ISBN:
(纸本)354020721X
A new system CMODELS-2 which is able to fix ASSAT's disadvantages was presented. It was found that the new system organizes the search process more efficiently than ASSAT as it does not explore the same part of the search tree more than once. the input language of CMODELS is generated by the preprocessor LPARSE. CMODELS is an answer set solver that uses SAT solvers as search engines.
logicprogramming has been used as a natural framework to automate deduction in the logic of order-of-magnitude reasoning. Specifically, we introduce a Prolog implementation of the Rasiowa-Sikorski proof system associ...
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logicprogramming has been used as a natural framework to automate deduction in the logic of order-of-magnitude reasoning. Specifically, we introduce a Prolog implementation of the Rasiowa-Sikorski proof system associated withthe relational translation Re(OM) of the multi-modal logic of order-of-magnitude qualitative reasoning OM.
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