He has been working with computer media since 1984 as an artist, designer, animator, computer programmer, and teacher. His work has been published in more than twenty countries, and he frequently lectures on new media around the world. In our method an event is an ordered pair of two consecutive states. Fast adaptation can be used to separate time scales of learning the value functions of a Markovian decision making problem and adaptation, the utilization of a non-Markovian policy. Computer simulations of a two-link pendulum with coarse discretization and noisy controller are shown to demonstrate the principle.
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There are numerous reports on rhythmic coupling between separate brain networks. It has been proposed that this rhythmic coupling indicates exchange of information. So far, few computational models have been proposed which explore this principle and its potential computational benefits. A network reading the hippocampal output must inevitably also receive an oscillatory theta input in order to decipher the phase coded firing patterns. In this work I propose a simple physiologically plausible mechanism implemented as an oscillatory network which can decode the hippocampal output.