40,097 research outputs found
Innovative Education, President\u27s Progress Report 2017
How can academic leadership create a culture of INNOVATION?
How can faculty more effectively convey their KNOWLEDGE?
How can students learn the skills, traits, and process to become future INNOVATORS
Introduction to TIPS: a theory for creative design
A highly intriguing problem in combining artificial intelligence and engineering design is automation of the creative and innovative phases of the design process. This paper gives a brief introduction to the theory of inventive problem solving (TIPS) selected as a theoretical basis of the authors' research efforts in this field. The research is conducted in the Stevin Project of the Knowledge-Based System Group of the University of Twente (Enschede, The Netherlands) in cooperation with the Invention Machine Laboratory (Minsk, Belarus). This collaboration aims at developing a formal basis for the creation of an automated reasoning system to support creative engineering design
Optimization of Evolutionary Neural Networks Using Hybrid Learning Algorithms
Evolutionary artificial neural networks (EANNs) refer to a special class of
artificial neural networks (ANNs) in which evolution is another fundamental
form of adaptation in addition to learning. Evolutionary algorithms are used to
adapt the connection weights, network architecture and learning algorithms
according to the problem environment. Even though evolutionary algorithms are
well known as efficient global search algorithms, very often they miss the best
local solutions in the complex solution space. In this paper, we propose a
hybrid meta-heuristic learning approach combining evolutionary learning and
local search methods (using 1st and 2nd order error information) to improve the
learning and faster convergence obtained using a direct evolutionary approach.
The proposed technique is tested on three different chaotic time series and the
test results are compared with some popular neuro-fuzzy systems and a recently
developed cutting angle method of global optimization. Empirical results reveal
that the proposed technique is efficient in spite of the computational
complexity
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
In this paper we describe how MAP inference can be used to sample efficiently
from Gibbs distributions. Specifically, we provide means for drawing either
approximate or unbiased samples from Gibbs' distributions by introducing low
dimensional perturbations and solving the corresponding MAP assignments. Our
approach also leads to new ways to derive lower bounds on partition functions.
We demonstrate empirically that our method excels in the typical "high signal -
high coupling" regime. The setting results in ragged energy landscapes that are
challenging for alternative approaches to sampling and/or lower bounds
What can we do with the Research Institute for Social Complexity Sciences in Indonesia?
The article discussed about the research opportunities in social complexity studies, especially in Indonesia. This issue is connected to the establishment a social research institute in Indonesia, how to establish and maintain it regarding the interdisciplinary research field. However a lot of localities are taken into the consideration to maintain the social complexity research institute, there would always things that can be learnt by any other similar research institute
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