******************Aim and Scope*******************

The aim of JELIA 2016 is to bring together active researchers interested in all aspects concerning the use of logics in Artificial Intelligence to discuss current research, results, problems, and applications of both theoretical and practical nature. JELIA strives to foster links and facilitate cross-fertilization of ideas among researchers from various disciplines, among researchers from academia and industry, and between theoreticians and practitioners.

Authors are invited to submit papers presenting original and unpublished research in all areas related to the use of logics in Artificial Intelligence including:

*Abductive and inductive reasoning
*Answer set programming
*Applications of logic-based AI systems
*Argumentation systems
*Automated reasoning including satisfiability checking and its extensions
*Computational complexity and expressiveness
*Deontic logic and normative systems
*Description logics and other logical approaches to semantic web and ontologies
*Knowledge representation, reasoning, and compilation
*Logic-based data access and integration
*Logic programming and constraint programming
*Logics for uncertain and probabilistic reasoning
*Logics in machine learning
*Logics in multi-agent systems, games, and social choice
*Non-classical logics, such as modal, temporal, epistemic, dynamic, spatial, paraconsistent, and hybrid logics
*Planning and diagnosis based on logic Preferences
*Reasoning about actions and causality
*Updates, belief revision and nonmonotonic reasoning

Special Track
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This year's conference will include a Special Track on "Logic in AI and Cognition", focusing on the use of logics that seek to describe (not prescribe) human cognition, and that can be used for the design of systems that learn, reason, and interact with humans in a natural manner. Topics of interest for this Special Track include:

*Logic and natural language
*Cognitive knowledge representation and context
*Automating commonsense reasoning
*Algorithms and data structures for logic-based reasoning at a massive scale
*Tradeoffs between representational expressivity and reasoning/learning efficiency
*Interaction of logics with connectionist/neural approaches
*Conflict resolution across different knowledge bases
*Psychologically-inspired logics and psychological evaluation of logics