Formal logical tools are able to provide some amount of reasoning support for information analysis, but are unable to represent uncertainty. Bayesian network tools represent probabilistic and causal information, but in the worst case scale as poorly as some formal logical systems and require specialized expertise to use effectively. We describe a framework for systems that incorporate the advan...

We present λ→2, a concise formulation of a proof term calculus for the intuitionistic modal logic S4 that is well-suited for practical applications. We show that, with respect to provability, it is equivalent to other formulations in the literature, sketch a simple type checking algorithm, and prove subject reduction and the existence of canonical forms for well-typed terms. Applications includ...

The issues of joint use of neural network technologies with methods of logical deduction and decision making support in data mining tasks are considered. The analysis of searching for logical patterns algorithms, their advantages and disadvantages is carried out. The description of combined algorithms for rules extraction from the trained neural networks and presentation the result in the form ...

The paper that introduced shape analysis sentences presented a method for extracting a sentence in first-order logic that completely characterizes a run of cpsa. Logical deduction can then be used to determine if a security goal is satisfied. This paper presents a method for importing shape analysis sentences into a proof assistant on top of a detailed theory of strand spaces. The result is a s...

In this paper, we present a modelling of tree filtering mechanisms in logical-based grammars. This filtering permits restriction of the excessive generative capacity of syntactic parsing grammars. In order to preserve the declarative aspect of natural language grammars, we consider syntactic parsing as a deduction process; tree filtering consists in the reduction of the allowed forms of the pro...

A series of hypotheses is proposed, connecting neural structures and dynamics with the formal structures and processes of probabilistic logic. First, a hypothetical connection is proposed between Hebbian learning in the brain and the operation of probabilistic term logic deduction. It is argued that neural assemblies could serve the role of logical terms; synapse-bundles joining neural assembli...

Intelligent systems can be modeled by organizationally closed networks of interacting agents. An interesting step in the evolution from agents to systems of agents is to approach logic itself as a system of autonomous elementary processes called distinctions. Distinction networks are directed acyclic graphs in which links represent logical implication and nodes are autonomous agents which act i...

A temporal logic of belief and actions (TLBA) is considered. The TLBA allows us to express informational and dynamic properties of computational agents. The considered fragment of TLBA allows one: (1) to present a deduction-based structured decision procedure; (2) to separate a decision procedure for so-called induction-free formulas and (3) to use only logical axioms for such formulas. The mai...

Proof search for the structural synthesis of programs (SSP) — a deductive program synthesis method which is suited for compositional programming in large and is in practical use in a number of programming environments is explained. SSP is based on a decidable logical calculus where complexity of the proof search is still PSPACE. This requires paying special attention to the efficiency of search...

In previous work, Levesque proposed an extension to classical databases that would allow for a certain form of incomplete first-order knowledge. Since this extension was sufficient to make full logical deduction undecidable, he also proposed an alternative reasoning scheme with desirable logical properties. He also claimed (without proof) that this reasoning could be implemented efficiently usi...