AI Education Matters: Teaching Hidden Markov Models

In this column, we share resources for learning about and teaching Hidden Markov Models (HMMs). HMMs find many important applications in temporal pattern recognition tasks such as speech/handwriting/gesture recognition and robot localization. In such domains, we may have a finite state machine model with known state transition probabilities, state output probabilities, and state outputs, but lack knowledge of the states generating such outputs. HMMs are useful in framing problems where external sequential evidence is used to derive underlying state information (e.g. intended words and gestures). [excerpt

A Developmental Organization for Robot Behavior

This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions of dynamic pattern theory in which behavior is an artifact of coupled dynamical systems with a number of controllable degrees of freedom. In our model, the events that delineate control decisions are derived from the pattern of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential knowledge gathering and representation tasks and provide examples of the kind of developmental milestones that this approach has already produced in our lab

Specialization, Information, and Growth: A Sequential Equilibrium Analysis

Pricing costs and information problems are introduced into a framework with consumer-producers, economies of specialization, and transaction costs to predict the endogenous and concurrent evolution in division of labor and in the information of organization acquired by society. The concurrent evolution generates endogenous growth based on the tradeoff between gains from information about the efficient pattern of division of labor, which can be acquired via experiments with various patterns of division of labor, and experimentation costs, which relate to the costs in discovering prices. The concept of Walras sequential equilibrium is developed to analyze the social learning process which is featured with uncertainties of the direction of the evolution as well as a certain trend of the evolution.Coevolution of specialization and information, adaptive decision, bounded rationality, sequential equilibrium, economic development.

Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light

One of the solutions of depth imaging of moving scene is to project a static pattern on the object and use just a single image for reconstruction. However, if the motion of the object is too fast with respect to the exposure time of the image sensor, patterns on the captured image are blurred and reconstruction fails. In this paper, we impose multiple projection patterns into each single captured image to realize temporal super resolution of the depth image sequences. With our method, multiple patterns are projected onto the object with higher fps than possible with a camera. In this case, the observed pattern varies depending on the depth and motion of the object, so we can extract temporal information of the scene from each single image. The decoding process is realized using a learning-based approach where no geometric calibration is needed. Experiments confirm the effectiveness of our method where sequential shapes are reconstructed from a single image. Both quantitative evaluations and comparisons with recent techniques were also conducted.Comment: 9 pages, Published at the International Conference on Computer Vision (ICCV 2017

Gaya Belajar Mahasiswa Reguler Angkatan 2005 Program Sarjana Keperawatan Universitas Jenderal Soedirman Purwokerto

Understanding toward learning process and students\u27learning-achievement need knowledge about how someone learns. Learning style early detection helps students to understand their owned learning modalities. Learning style is a combination of how individual perceive, manage and process information. The goal of this research was to understand learning style description (learning modalities and brain\u27s domination) which dominantly existed in students of regular undergraduate nursing program 2005 enrollment. Survey method was used in this research which included 51 participants from regular undergraduate nursing program 2005 enrollment as sample. Purposive sampling was used. This research conducted in May to June 2006. Result showed that learning modalities in students of regular undergraduate program 2005 enrolment were visual (43,1 %), auditory (29,4%), kinesthetic (15,7 %), visual-auditory (2%), visual-kinesthetic (3,9%), auditory-kinesthetic (3,9%), and visual-auditory-kinesthetic (2%). Besides, brain domination pattern they owned were abstract non-linear/AA (43,1 %), sequential-concrete/SK (29,4%), sequential-abstract/SA (9,8%), combination SK-SA /sequential (5,9%), concrete non-linear (3,9%) balance all (3,9%) non linear/combination AA-AK (2%), and concrete/combination SK-AA (22%) The learning style involved learning modalities and brain\u27s domination . The students of regular undergraduate nursing program 2005 enrollment, had the learning modalities that was dominated with visual (43,1%). They also had abstract- non linear of brain\u27s domination, equal to 43,1%