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The Cricket Location-Support System

by Nissanka B. Priyantha, Anit Chakraborty, Hari Balakrishnan , 2000
"... This paper presents the design, implementation, and evaluation of Cricket, a location-support system for in-building, mobile, locationdependent applications. It allows applications running on mobile and static nodes to learn their physical location by using listeners that hear and analyze informatio ..."
Abstract - Cited by 1058 (11 self) - Add to MetaCart
This paper presents the design, implementation, and evaluation of Cricket, a location-support system for in-building, mobile, locationdependent applications. It allows applications running on mobile and static nodes to learn their physical location by using listeners that hear and analyze

Predictive reward signal of dopamine neurons

by Wolfram Schultz - Journal of Neurophysiology , 1998
"... Schultz, Wolfram. Predictive reward signal of dopamine neurons. is called rewards, which elicit and reinforce approach behav-J. Neurophysiol. 80: 1–27, 1998. The effects of lesions, receptor ior. The functions of rewards were developed further during blocking, electrical self-stimulation, and drugs ..."
Abstract - Cited by 747 (12 self) - Add to MetaCart
conditions. that resemble reward-predicting stimuli or are novel or particularly Rewards come in various physical forms, are highly variable salient. However, only few phasic activations follow aversive stim-in time and depend on the particular environment of the subject. uli. Thus dopamine neurons label

The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity

by Clay B. Holroyd, Michael G. H. Coles - PSYCHOLOGICAL REVIEW 109:679–709 , 2002
"... The authors present a unified account of 2 neural systems concerned with the development and expression of adaptive behaviors: a mesencephalic dopamine system for reinforcement learning and a “generic ” error-processing system associated with the anterior cingulate cortex. The existence of the error ..."
Abstract - Cited by 430 (20 self) - Add to MetaCart
of the error-processing system has been inferred from the error-related negativity (ERN), a component of the event-related brain potential elicited when human participants commit errors in reaction-time tasks. The authors propose that the ERN is generated when a negative reinforcement learning signal

Developments in the Measurement of Subjective Well-Being

by Daniel Kahneman , Alan B Krueger - Psychological Science. , 1993
"... F or good reasons, economists have had a long-standing preference for studying peoples' revealed preferences; that is, looking at individuals' actual choices and decisions rather than their stated intentions or subjective reports of likes and dislikes. Yet people often make choices that b ..."
Abstract - Cited by 284 (7 self) - Add to MetaCart
that bear a mixed relationship to their own happiness. A large literature from behavioral economics and psychology finds that people often make inconsistent choices, fail to learn from experience, exhibit reluctance to trade, base their own satisfaction on how their situation compares with the satisfaction

Reinforcement Learning or Active Inference?

by Karl J. Friston, Jean Daunizeau, Stefan J. Kiebel , 2009
"... This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sam ..."
Abstract - Cited by 9 (2 self) - Add to MetaCart
This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states

Fish‘n’Steps: Encouraging Physical Activity with an Interactive Computer Game

by James J. Lin, Lena Mamykina, Silvia Lindtner, Gregory Delajoux, Henry B. Strub - Proceedings of UbiComp’06 , 2006
"... Abstract. A sedentary lifestyle is a contributing factor to chronic diseases, and it is often correlated with obesity. To promote an increase in physical activity, we created a social computer game, Fish'n'Steps, which links a player’s daily foot step count to the growth and activity of an ..."
Abstract - Cited by 162 (1 self) - Add to MetaCart
, by that time, established new routines that led to healthier patterns of physical activity in their daily lives. Lessons learned from this study underscore the value of such games to encourage rather than provide negative reinforcement, especially when individuals are not meeting their own expecta-tions

Activity Sensing in the Wild: A Field Trial of UbiFit Garden

by Sunny Consolvo, David W. McDonald, Tammy Toscos, Mike Y. Chen, Jon Froehlich, Beverly Harrison, Predrag Klasnja, Anthony LaMarca, Louis LeGrand, Ryan Libby, Ian Smith, James A. Landay - PROC. OF CHI’08 , 2008
"... Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people’s activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, Ub ..."
Abstract - Cited by 160 (9 self) - Add to MetaCart
Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people’s activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system

Brain-machine interface control via reinforcement learning

by Jack Digiovanna, Student Member, Babak Mahmoudi, Student Member, Jeremiah Mitzelfelt, Justin C. Sanchez, Jose C. Principe - in Proc. 3rd Int. IEEE EMBS Conf. Neural Engineering, Kohala , 2007
"... Abstract — We investigate the capabilities of reinforcement learning (RL) to create a brain-machine interface (BMI) that uses Q(λ) learning to find the functional mapping between neural activity and intended behavior. This paradigm shift is intended to address the issue of paralyzed and amputee pati ..."
Abstract - Cited by 12 (5 self) - Add to MetaCart
Abstract — We investigate the capabilities of reinforcement learning (RL) to create a brain-machine interface (BMI) that uses Q(λ) learning to find the functional mapping between neural activity and intended behavior. This paradigm shift is intended to address the issue of paralyzed and amputee

Behavioral theories and the neurophysiology of reward,

by Wolfram Schultz - Annu. Rev. Psychol. , 2006
"... ■ Abstract The functions of rewards are based primarily on their effects on behavior and are less directly governed by the physics and chemistry of input events as in sensory systems. Therefore, the investigation of neural mechanisms underlying reward functions requires behavioral theories that can ..."
Abstract - Cited by 187 (0 self) - Add to MetaCart
, without attempting to provide a complete account of all the studies done. We focus on the activity of single neurons studied by neurophysiological techniques in behaving animals, in particular monkeys, and emphasize the formative role of behavioral theories, such as animal learning theory

Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from tex

by Danielle S. Mcnamara, Eileen Kintsch, Nancy Butler Songer, Walter Kintsch - Institute of Cognitive Science , 1993
"... Two experiments, theoretically motivated by the construction-integration model of text comprehension ( W. Kintsch, 1988), investigated the role of text coherence in the comprehension of science texts. In Experiment 1, junior high school students' comprehension of one of three versions of a biol ..."
Abstract - Cited by 157 (13 self) - Add to MetaCart
biology text was examined via free recall, written questions, and a key-word sorting task. This study demonstrates advantages for globally coherent text and for more explanatory text. In Experiment 2, interactions among local and global text coherence, readers' background knowledge, and levels
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