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ICML
2009
IEEE
14 years 8 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino
EDUTAINMENT
2008
Springer
13 years 9 months ago
Teaching Machine Learning to Design Students
Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge t...
Bram van der Vlist, Rick van de Westelaken, Christ...
ECAI
2008
Springer
13 years 9 months ago
Fighting Knowledge Acquisition Bottleneck with Argument Based Machine Learning
Knowledge elicitation is known to be a difficult task and thus a major bottleneck in building a knowledge base. Machine learning has long ago been proposed as a way to alleviate th...
Martin Mozina, Matej Guid, Jana Krivec, Aleksander...
SEAL
1998
Springer
14 years 3 days ago
Using Genetic Algorithms to Simulate the Evolution of an Oligopoly Game
Abstract. This paper extends the N-person IPD game into a more interesting game in economics, namely, the oligopoly game. Due to its market share dynamics, the oligopoly game is mo...
Shu-Heng Chen, Chih-Chi Ni
ICML
2010
IEEE
13 years 9 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov