Special Issue on Commonsense Reasoning - Call for Papers

[geoff at cs.miami.edu]

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