SOLAR: A Consequence Finding System for Advanced Reasoning

Nabeshima, Hidetomo; Iwanuma, Koji; Inoue, Katsumi

doi:10.1007/978-3-540-45206-5_22

Cited by 25 publications

(17 citation statements)

References 7 publications

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“…SOLAR [2] is a sophisticated deductive reasoning system based on SOL-resolution [8], which is sound and complete for finding minimal consequences belonging to a given language bias (a production field). Consequence-finding by SOLAR is performed by skipping literals belonging to a production field P instead of resolving them.…”

Section: Computation Through Hypothesis Findingmentioning

confidence: 99%

“…SOLAR is designed for full clausal theories containing non-Horn clauses, and is based on a connection tableau format [10]. In this format, many redundant deductions are avoided using various state-of-the-art pruning techniques [2], thereby hypothesis-finding is efficiently realized.…”

Section: Computation Through Hypothesis Findingmentioning

confidence: 99%

“…For such situations, we presented in [1] a sound mechanism that is guaranteed to find an abductive hypotheses with respect to distributed full clausal theories whenever one exists. This Multi-agent Abductive Reasoning System, MARS, is based on a consequence finding tools named SOLAR [2], that serves as a main reasoning engine. We are concerned in this paper with the efficiency of this mechanism, and thus want to evaluate and improve its average computational and communicational cost.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Towards Efficient Multi-agent Abduction Protocols

Bourgne

Inoue

Maudet

2011

Languages, Methodologies, and Development Tools for Multi-Agent Systems

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Abstract-What happens when distributed sources of information (agents) hold and acquire information locally, and have to communicate with neighbouring agents in order to refine their hypothesis regarding the actual global state of this environment? This question occurs when it is not be possible (e. g. for practical or privacy concerns) to collect observations and knowledge, and centrally compute the resulting theory. In this paper, we assume that agents are equipped with full clausal theories and individually face abductive tasks, in a globally consistent environment. We adopt a learner/critic approach. We present the Multi-agent Abductive Reasoning System (MARS), a protocol guaranteeing convergence to a situation "sufficiently" satisfying as far as consistency of the system is concerned. Abduction in a full clausal theory has however already a high computational cost in centralized settings, which can become much worse with arbitrary distributions. We thus discuss ways to use knowledge about each agent's theory language to improve efficiency. We then present some first experimental results to assess the impact of those refinements.

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Section: Computation Through Hypothesis Findingmentioning

confidence: 99%

Section: Computation Through Hypothesis Findingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Towards Efficient Multi-agent Abduction Protocols

Bourgne

Inoue

Maudet

2011

Languages, Methodologies, and Development Tools for Multi-Agent Systems

Self Cite

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“…Most of them are designed for propositional logic only [13,19] and are not very efficient in solving equational problems (con-verted beforehand to propositional logic) [5,6]. Others are not well suited for comparison with our tool, either for lack of completeness [4] or because they do not handle equality [15]. This is why, to evaluate the efficiency of the constrained calculus (CC), we integrated it in our tool Kparam (see [5,6]) and compared it 7 with the calculus from [6] (Kp) on a thousand of randomly generated benchmarks containing up to 6 clauses of maximum 5 literals made from 8 constants.…”

Section: Methodsmentioning

confidence: 99%

“…These algorithms use either refinements of the Resolution calculus 1 or decomposition procedures in the spirit of the DPLL method. Other approaches have tackled more expressive logics [2,10,11,14,15]. In [6,5] we devised an algorithm to generate implicates of ground, functionfree equational clause sets, i.e.…”

Section: Introductionmentioning

confidence: 99%

A Deductive-Complete Constrained Superposition Calculus for Ground Flat Equational Clauses

Tourret¹,

Echenim²,

Peltier³

EPiC Series in Computing

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We describe an algorithm that generates prime implicates of equational clause sets without variables and function symbols. The procedure is based on constrained superposition rules, where constraints are used to store literals that are asserted as additional axioms (or hypotheses) during the proof search. This approach is sound and deductive-complete, and it is more efficient than previous algorithms based on conditional paramodulation. It is also more flexible in the sense that it allows one to restrict the search space by imposing additional properties that the generated implicates should satisfy (e.g., to ensure relevance).

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