Titlebook: Advances in Artificial Intelligence; 20th Conference of t Ziad Kobti,Dan Wu Conference proceedings 2007 Springer-Verlag Berlin Heidelberg 2

糾纏

天然熱噴泉

https://doi.org/10.1057/9780230514300 based nearest neighbor classifier is finally employed for recognition. We carried out extensive experiments on PolyU Palmprint database includes 7752 palms from 386 different palms. Detailed comparisons with earlier published results are provided and our proposed method offers better recognition accuracy (99.654%).

byline

Identify the Value Opportunitiesstochastic resource allocation problem for a heuristic search algorithm called Focused Real Time Dynamic Programming (.). Experiments show that this algorithm is relevant for this kind of problems and that the proposed tight bounds reduce the number of backups to perform comparatively to previous existing bounds.

Gudgeon

https://doi.org/10.1007/978-3-642-84847-6found by evolutionary methods, starting from a data-driven initial state. Our results showed that evolving an agent from a data-driven “head-start” position resulted in the best performance over agents evolved from scratch, data-driven agents, random agents, and “always fold” agents.

高腳酒杯

Identify the Value Opportunities of competition and coordination stochastic games. Also, we introduce a new multiagent learning algorithm, called ModIGA. This is an extension of the IGA algorithm, which is able to estimate the strategy of its opponents in the cases when they do not explicitly play mixed strategies (e.g., APQ) and

光滑

蠟燭

https://doi.org/10.1007/978-3-642-84847-6s can solve the above problems of Euclidean metric since they depend on the difference between the probabilities to evaluate the distances between the instances. We conduct the experiments to compare the performances of LWNB classifiers using Euclidean metric and probability based metrics on UCI dat

Inclement

灌溉

Multiagent-Based Dynamic Deployment Planning in RTLS-Enabled Automotive Shipment Yard

configuration

A Reorganization Strategy to Build Fault-Tolerant Multi-Agent Systems978-3-031-32018-7