About the Journal

Logic has found application in virtually all aspects of Information Technology, from software engineering and hardware to programming and artificial intelligence. Indeed, logic, artificial intelligence and theoretical computing are influencing each other to the extent that a new interdisciplinary area of Logic and Computation is emerging.

The Journal of Logic and Computation is an online only publication aiming to promote the growth of logic and computing, including, among others, the following areas of interest: Logical Systems, such as classical and non-classical logic, constructive logic, categorical logic, modal logic, type theory, feasible maths.... Logical issues in logic programming, knowledge-based systems and automated reasoning; logical issues in knowledge representation, such as non-monotonic reasoning and systems of knowledge and belief; logics and semantics of programming; specification and verification of programs and systems; applications of logic in hardware and VLSI, natural language, concurrent computation, planning, and databases. The bulk of the content is technical scientific papers, although letters, reviews, and discussions, as well as relevant conference reviews, are included.

Special Issue on Proof-Theoretic Semantics and Computation
Submission Date: 2026-03-31

Guest Editors:

Sara Ayhan (Ruhr University Bochum)
Alexander V. Gheorghiu (University of Southampton & UCL)
Will Stafford (Kansas State University)
Submission Deadline

31st of March 2026

Proof-theoretic semantics (P-tS) offers a foundational shift in logic, prioritizing inference over truth conditions and emphasizing the centrality of proof in the assignment of meaning. This inferential perspective is naturally aligned with computational approaches, yet the intersection of P-tS and computation remains comparatively underexplored.

This special issue of the Journal of Logic and Computation seeks to fill that gap by bringing together work at the interface of logic, computer science, and philosophy. We invite contributions that illuminate how computational interpretations of logic interact with proof-theoretic approaches, both conceptually and practically.

Topics of Interest include (but are not limited to):

The computational content of proof-theoretic semantics
Type theory (simple, dependent, homotopy, cubical, inductive, etc.)
The Curry–Howard correspondence and computational interpretations of logic
Definitional reflection, inversion principles, and normalization
Reductive logic, proof-search, and logic programming
Automated and interactive theorem proving
Inductive and coinductive types, and (co)algebraic semantics
Term rewriting systems and proof-term transformation
Realizability semantics and connections to constructive logics
Proof mining and quantitative information extraction
Formal verification of software, hardware, and algorithms
Proof simplicity, identity, and Hilbert’s 24th problem
Applications in computational linguistics and type-logical grammars
Logic-based AI and explainable reasoning systems

Submissions must engage substantively with the ideas of proof-theoretic semantics and their relevance to computational practice. Work that treats computational topics in isolation, without connection to P-tS, will not be considered.

Special Issue on Combining Probability and Logic
Submission Date: 2026-03-31

Guest Editors

Krzysztof Mierzewski (Carnegie Mellon University)

Francesca Zaffora Blando (Carnegie Mellon University)
Submission deadline: 31st March 2026

We invite submissions for a Special Issue on “Combining Probability and Logic”, to be published in the Journal of Logic and Computation.

Probability and logic provide two distinct frameworks for modeling how rational agents ought to draw inferences and learn from the available data in the face of uncertainty. We solicit submissions of original papers that bridge these two perspectives.

In particular, we especially welcome submissions that combine insights and techniques from probability and logic to provide an analysis of rational learning and the conditions under which successful inductive learning can be achieved. These analyses may feature logic both in the strict sense—involving the study of formal systems and their semantics to investigate questions of expressivity, complexity, knowledge representation and inference—and in the broader sense of a systematic theory of correct reasoning and rational learning.

Topics of interest include, but are not limited to, logical and computability-theoretic aspects of probabilistic inference, logics for probabilistic and causal reasoning, inductive logic, statistical models of learning (including Bayesian approaches), formal learning theory, and topological approaches to learning and learnability. The Special Issue is related to the topics of the conference Progic 2025: The 12th Workshop on Combining Probability and Logic. Workshop participants as well as other authors are invited to submit a contribution.