Most research on adaptive decision-making takes a strategyfirst approach, proposing a method of solving a problem and then examining whether it can be implemented in the brain and in what environments it succeeds. We present a method for studying strategy development based on computational evolution that takes the opposite approach, allowing strategies to develop in response to the decision-mak...

Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and ...

Post pruning of decision trees has been a successful approach in many real-world experiments, but over all possible concepts it does not bring any inherent improvement to an algorithm's performance. This work explores how a PAC-proven decision tree learning algorithm fares in comparison with two variants of the normal top-down induction of decision trees. The algorithm does not prune its hypoth...

The principle of multicriterial decision-making is used for the purpose of autonomous control of both individual agent and the multiagent team as a whole. This approach to the realization of control mechanism is non-standard and experimental and the robot soccer game was chosen as a testing ground for this control method. It provides an area for further study and research and some of the detail...

Supplier selection is a major strategy for manufacture to run the production process smoothly. Supplier categorization, selection and performance evaluation are decisions of strategic importance to companies. Global competition, mass customization, high customer expectations and harsh economic conditions are forcing companies to rely on external suppliers to contribute a larger portion of parts...