This paper describes one of the future images of the sleep monitoring system. The new technology should satisfy the following requirements: (1) noninvasive, (2) low cost and (3) long-term monitoring. What we propose here is the sleep monitoring system based on the human body vibrations sensed by the mattress type pressure sensors that gradually improves its estimation performance to the particular user by learning collected data and reconstructing its classifier.%In order to learn the data, however, the system needs the vibration data mapped to the appropriate sleep stages. As the solution to the problem, we use the existing approximate sleep stage estimation method. The experimental results reveal that (1)there is only a slightly difference between the accuracies of the two classifiers; the one trained the original dataset plus PSG based sleep stage labeled data; the other one trained the original dataset plus approximate sleep stage labeled data; (2 )Adding a particular user's several days data to the training data improves the accuracy of the original classifiers. The REM estimation accuracy is 87% in maximum. From those results, the contribution of this research is suggesting the way to personalize sleep estimation, and proving the effectiveness.

This paper reports a cradle sound system creating and reproducing sounds and music appropriate for human sleep with heartbeat and respiration signals sensed by biological sensors. To get further supporting evidence, we started a study aiming at exploring what sound attributes, such as waveforms, tones, and tempos, are necessary for a sound capable of improving sleep latency. We expected that a cradle sound whose tempo was slightly slower than those of heartbeat and respiration could slow them and could promote natural sleep. Subjects listening to this sound during their sleep showed: (1) Multiple sound types with different tones have an effect to shorten sleep latency. (2) Remarkable effects are observed in subjects with long sleep latency. (3) Sustained synthetic chord used for inducing respiration did not improve sleep latency. (4) There is no correlation between subject’s sensibility evaluation to sound and the effect shortening sleep latency.

The AAAI 2015 Spring Symposium Series was held Monday through Wednesday, March 23-25, at Stanford University near Palo Alto, California. The titles of the seven symposia were Ambient Intelligence for Health and Cognitive Enhancement, Applied Computational Game Theory, Foundations of Autonomy and Its (Cyber) Threats: From Individuals to Interdependence, Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Logical Formalizations of Commonsense Reasoning, Socio-Technical Behavior Mining: From Data to Decisions, Structured Data for Humanitarian Technologies: Perfect Fit or Overkill?

The AAAI 2015 Spring Symposium Series was held Monday through Wednesday, March 23-25, at Stanford University near Palo Alto, California. The titles of the seven symposia were Ambient Intelligence for Health and Cognitive Enhancement, Applied Computational Game Theory, Foundations of Autonomy and Its (Cyber) Threats: From Individuals to Interdependence, Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Logical Formalizations of Commonsense Reasoning, Socio-Technical Behavior Mining: From Data to Decisions, Structured Data for Humanitarian Technologies: Perfect Fit or Overkill? and Turn-Taking and Coordination in Human-Machine Interaction.The highlights of each symposium are presented in this report.

This paper aims at developing the ambient intelligence sleep system that can derive a good sleep by providing a personally adapted sound. For this purpose, this paper explores the sounds that have a potential of deriving a good sleep and investigates their effect from the several viewpoints (e.g., the sleep latent time). To promote a good sleep, this paper focuses on heartbeat and respiration which are related to a sleep (i.e., its rate decreases as falling asleep) and proposes the ambient intelligent sleep system that provides the sound adjusted to the heartbeat and/or respiration rates, which are automatically measured by the piezoelectric-based mattress sensor without connecting any devices to human’s body. The human subjective experiments of the six subjects for a nap case and the seven subjects for a night sleep case have revealed the following implications: (1) the new wave sound adjusted to both the heartbeat rate (x 1.05) and respiration rate (x 1.05) can shorten the sleep latent time in a nap case in comparison with no sound or the other four types of the sounds; (2) the combination of the two sound sources (adjusted by the heartbeat and respiration rates) contributes to shortening the sleep latent time in comparison with one sound source; (3) the new wave sound can shorten not only the sleep latent time but also the Non-REM3 latent time in a night sleep case in comparison with no sound; and (4) the new wave sound can keep not only an appropriate sleep cycle but also the very similar sleep cycle from the Non-REM to the next one in a night sleep case in comparison with no sound.

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2014 Spring Symposium Series, held Monday through Wednesday, March 24–26, 2014. The titles of the eight symposia were Applied Computational Game Theory, Big Data Becomes Personal: Knowledge into Meaning, Formal Verification and Modeling in Human-Machine Systems, Implementing Selves with Safe Motivational Systems and Self-Improvement, The Intersection of Robust Intelligence and Trust in Autonomous Systems, Knowledge Representation and Reasoning in Robotics, Qualitative Representations for Robots, and Social Hacking and Cognitive Security on the Internet and New Media). This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2014 Spring Symposium Series, held Monday through Wednesday, March 24–26, 2014. The titles of the eight symposia were Applied Computational Game Theory, Big Data Becomes Personal: Knowledge into Meaning, Formal Verification and Modeling in Human-Machine Systems, Implementing Selves with Safe Motivational Systems and Self-Improvement, The Intersection of Robust Intelligence and Trust in Autonomous Systems, Knowledge Representation and Reasoning in Robotics, Qualitative Representations for Robots, and Social Hacking and Cognitive Security on the Internet and New Media). This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2013 Spring Symposium Series, held Monday through Wednesday, March 25-27, 2013. The titles of the eight symposia were Analyzing Microtext, Creativity and (Early) Cognitive Development, Data Driven Wellness: From Self-Tracking to Behavior Change, Designing Intelligent Robots: Reintegrating AI II, Lifelong Machine Learning, Shikakeology: Designing Triggers for Behavior Change, Trust and Autonomous Systems, and Weakly Supervised Learning from Multimedia. This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2013 Spring Symposium Series, held Monday through Wednesday, March 25-27, 2013. The titles of the eight symposia were Analyzing Microtext, Creativity and (Early) Cognitive Development, Data Driven Wellness: From Self-Tracking to Behavior Change, Designing Intelligent Robots: Reintegrating AI II, Lifelong Machine Learning, Shikakeology: Designing Triggers for Behavior Change, Trust and Autonomous Systems, and Weakly Supervised Learning from Multimedia. This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2012 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2012 at Stanford University, Stanford, California USA. The six symposia held were AI, The Fundamental Social Aggregation Challenge (cochaired by W. F. Lawless, Don Sofge, Mark Klein, and Laurent Chaudron); Designing Intelligent Robots (cochaired by George Konidaris, Byron Boots, Stephen Hart, Todd Hester, Sarah Osentoski, and David Wingate); Game Theory for Security, Sustainability, and Health (cochaired by Bo An and Manish Jain); Intelligent Web Services Meet Social Computing (cochaired by Tomas Vitvar, Harith Alani, and David Martin); Self-Tracking and Collective Intelligence for Personal Wellness (cochaired by Takashi Kido and Keiki Takadama); and Wisdom of the Crowd (cochaired by Caroline Pantofaru, Sonia Chernova, and Alex Sorokin). The papers of the six symposia were published in the AAAI technical report series.