August 4, 2013, Beijing, China

Artificial Intelligence research has made substantial progress since the 1950s. However, many state-of-the-art intelligent systems are still not able to outperform human intelligence. To advance the research in artificial intelligence, it is beneficial to investigate intelligence, both artificial and natural, in an interdisciplinary context. The objective of this workshop is to bring together researchers from brain science, cognitive science, and artificial intelligence to explore the essence and technology of intelligence. This workshop provides a platform to discuss some key issues in intelligence science:
(1) What new methodologies and ideas may cognitive science and brain science bring into the research of artificial intelligence?
(2) What are the underlying algorithmic principles and circuitry wiring of the observed intelligent behaviors?
(3) How are intelligent behaviors realized as hierarchical organization of functions across multiple modalities and time scales?
(4) What are the key problems of intelligence science that requires joint research in brain science, cognitive science, and artificial intelligence?

This workshop takes advantage of IJCAI-13 by hoping to attract participants from academia and industry worldwide. The communication among researchers from these fields will strongly boost the understanding of intelligence, provoke new theories on intelligent behaviors and lead to new experiments or systems.

The workshop is to be held at the beginning of IJCAI-13, August 4, 2013. Workshop participants will have the opportunity to meet and discuss issues with a selected focus — providing an informal setting for active exchange among researchers and developers on topics of common interest.

Topics of interest related to Intelligence Science include but are not limited to the following areas:

 Basic process of neural activity in brain
 ●Coding and retrieval of memory
 Learning and synaptic plasticity
 Thought and decision making
 Development and adaptation of intelligence
 Mind modeling
 Brain-machine integration
 Brain-like machine
 ●Fusion of machine intelligence and biological intelligence
 ●Perceptual representation and feature binding
 Linguistic cognition
 Exploration and active sampling
 Emotion and affection
 Nature of consciousness
 Cognitive computing and simulation
 Intelligent robots and animal robots
 ●Encoding and decoding of neural information
 ●Computational models for biological-machine systems

Submission Deadline :8 April, 2013

Acceptance Notification: 1 May, 2013

Final Version:20 May, 2013

Key Laboratory of Intelligent Information Processing
Institute of Computing Technology, Chinese Academy of Sciences