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A biologically inspired computational model of rodent repre-sentation?based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated p ...
Ultra-High Performance Fiber-Reinforced Concrete (UHPFRC) can be considered, due to its high strength and improved durability, as one of the leading recent innovations in civil engineering. Material scientists have developed a very efficient, high-tech mat ...
RATIONALE: To determine the suitability of the nine-hole box to characterise mouse performance on a free operant task and a discrete trials task, and to validate the tests by probing whether d-amphetamine and scopolamine modify performance of the task as p ...
Particle size should be optimized to achieve targeted and extended drug delivery to the affected tissues. We describe here the effects of the mean particle size on the pharmacokinetics and photothrombic activity of meso-tetra(carboxyphenyl)porphyrin (TCPP) ...
The Object Constraint Language (OCL) is based on rst- order logic and set theory. As the most well-known application, OCL is used to formulate well-formedness rules in the UML metamodel. Here, the transitive closure of a relationship is de ned in terms of ...
In this paper we compare Nash equilibria analysis and agent-based modelling for assessing the market dynamics of network-constrained pool markets. Power suppliers submit their bids to the market place in order to maximize their payoffs, where we apply rein ...
In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement-learning like abilities. The investigated tasks were generation and learning of short bit sequences. This "learning'' came about ...
Our research focuses on the behavioral animation of virtual humans who are capable of taking actions by themselves. We deal more specifically with reinforcement learning methodologies, which integrate in an original way the RL agent and the autonomous virt ...
We study spatial learning and navigation for autonomous agents. A state space representation is constructed by unsupervised Hebbian learning during exploration. As a result of learning, a representation of the continuous two-dimensional (2-D) manifold in t ...
Institute of Electrical and Electronics Engineers2004
The aims of the preliminary study reported in this document were twofold. Firstly, within the context of the application of UHPFRC for the rehabilitation of reinforced concrete structures, to identify the phenomena that require further study with respect t ...
