0000000000114804
AUTHOR
Vito Morreale
Goal-Oriented Development of BDI Agents: The PRACTIONIST Approach
The representation of goals and the ability to reason about them play an important role in goal-oriented requirements analysis and modelling techniques, especially in agent-oriented software engineering, as goals are more stable than other abstractions (e.g. user stories). In PRACTIONIST, a framework for developing agent systems according to the Belief-Desire-Intention (BDI) model, goals play a central role. Thus, in this paper we describe the structure of the goal model in the PRACTIONIST framework and how agents use their goal model to reason about goals, desires, and intentions during their deliberation process and means-ends reasoning as well as while performing their activities.
A Segmentation System for Soccer Robot Based on Neural Networks
An innovative technique for segmentation of color images is proposed. The technique implements an approach based on thresholding of the hue histogram and a feed-forward neural network that learns to recognize the hue ranges of meaningful objects. A new function for detecting valleys of the histogram has been devised and tested. A novel blurring algorithm for noise reduction that works effectively when used over hue image has been employed. The reported experimental results show that the technique is reliable and robust even in presence of changing environmental conditions. Extended experimentation has been carried on the framework of the Robot Soccer World Cup Initiative (RoboCup).