CALL FOR PAPERS

Special Issue on Commonsense Reasoning

Annals of Mathematics and Artificial Intelligence

We invite submissions to the Special Issue on Commonsense Reasoning of the journal Annals of Mathematics and Artificial Intelligence.

Papers should be submitted by June 30, 2018 via

http://www.editorialmanager.com/amai/

selecting the issue S692 Commonsense Reasoning.


Guest editors:

Andrew S. Gordon, University of Southern California
Rob Miller, University College London
Leora Morgenstern, Nuance
Gyorgy Turan, University of Illinois at Chicago, University of Szeged.

Endowing computers with common sense is one of the major long-term goals of Artificial Intelligence research. Commonsense knowledge and reasoning are relevant for many applications of current interest. Examples include robot and human collaboration, transparent machine-learning systems that can explain their conclusions, social media and story understanding software, and dialogue systems. The recent resurgence of interest in commonsense reasoning reflects recent technological advances which would greatly benefit from further progress in commonsense reasoning, and a wider societal reaction to these technological advances.

We welcome a wide variety of submissions on all relevant and rigorous approaches to acquiring commonsense knowledge and performing commonsense reasoning, including papers describing recent research and survey papers on the state of the art of research directions within the field.

Topics of interest include, but are not limited to

Semantics-based representations for specific commonsense domains, such as:

Time, change, action, causality
Commonsense physical and spatial reasoning
Legal, biological, medical, and other scientific reasoning incorporating elements of common sense
Mental states such as beliefs, intentions, and emotions
Social activities and relationships

Inference methods for commonsense reasoning, such as:

Logic programming
Probabilistic, heuristic, and approximate reasoning
Nonmonotonic reasoning, belief revision and argumentation
Abductive and inductive reasoning
Textual Entailment

Methods for creating commonsense knowledge bases, such as:

Statistical and corpus-based techniques, including both traditional machine learning and deep learning
Crowdsourcing
Hand-crafting domain theories
Hybrid methods

Applications of commonsense reasoning, especially interdisciplinary research in the following areas:

Natural language understanding (understanding discourse, question answering, semantic parsing)
Image understanding
Cognitive robotics and planning
Web-based applications (search, internet of things)
Support technologies (computer-aided instruction, home automation)

Discussions of the science of commonsense reasoning research, including:

Meta-theorems about commonsense theories and techniques
Relation to other fields, such as philosophy, linguistics, cognitive psychology, game theory, and economics
Challenge problem sets and benchmarking.

For more information, see http://commonsensereasoning.org