Is human thought fully embedded in language, or do some forms of thought operate independently? To directly address this issue, we focus on inference making, a central feature of human cognition. In a 3T fMRI study we compare logical inferences relying on sentential connectives (e.g., not, or, if..then..) to linguistic inferences based on syntactic transformation of sentences involving ditransi...

We propose a novel approach to the well-studied problem of making a finite, ordered sequence of decisions under uncertainty. Most existing work in this area concentrates on graphical representations of decision problems, and requires a complete specification of the problem. Our approach is based on a formal logic, such that the choice of an optimal decision can be treated as a problem of logica...

We propose a novel approach to the well-studied problem of making a finite, ordered sequence of decisions under uncertainty. Most existing work in this area concentrates on graphical representations of decision problems, and requires a complete specification of the problem. Our approach is based on a formal logic, such that the choice of an optimal decision can be treated as a problem of logica...

Is human thought fully embedded in language, or do some forms of thought operate independently? To directly address this issue, we focus on inference-making, a central feature of human cognition. In a 3T fMRI study we compare logical inferences relying on sentential connectives (e.g., not, or, if ... then) to linguistic inferences based on syntactic transformation of sentences involving ditrans...

The effective reasoning capability of an agent can be defined as its capability to infer, within a given space and time bound, facts that are logical consequences of its knowledge base. In this paper we show how to determine the effective reasoning capability of an agent with limited memory by encoding the agent as a transition system and automatically verifying whether a state where the agent ...

We present a proof-theoretic foundation for automated deduction in linear logic. At rst, we systematically study the permutability properties of the inference rules in this logical framework and exploit these to introduce an appropriate notion of forward and backward movement of an inference in a proof. Then we discuss the naturally-arising question of the redundancy reduction and investigate t...

We consider defining executable dialogues for communicating agents. Towards this end, we introduce agent classes whose communication primitives are based on deduction. Their operational semantics are given by an abstract logical machine that is defined purely in sequential terms. These agents communicate under the control of plans requiring a synchronization flag. These plans can be rewritten a...

We report on a case study in using logical frameworks to support the formalization of programming calculi and their application to deduction-based program synthesis. Within a conservative extension of higher-order logic implemented in the Isabelle system, we derived rules for program development that can simulate those of the deductive tableau proposed by Manna and Waldinger. We have used the r...

Many branches of computer science rely on logical formalisms as their foundations. Logic provides a very solid foundation on which to build new results: after 2500 years of research, logic provides us with a strong set of theoretical notions: model theory, proof theory, completeness, correctness; there exists a well established body of knowledge concerning properties such expressiveness, decida...

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...