A significant problem for case-based reasoning (CBR) systems is determining the features to use in judging case similarity for retrieval. We describe research that addresses the feature selection problem by using introspective reasoning to learn new features for indexing. Our method augments the CBR system with an introspective reasoning component which monitors system performance to detect poo...

In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...

We present a new multiagent model for the multiperiod portfolio selection problem. Individual agents receive a share of initial wealth, and follow an investment strategy that adjusts their portfolio as they observe movements of the market over time. The agents share their wealth at the end of the nal investment period. We show that a multiagent system can outperform a single agent that invests ...

User-to-user correlation is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user correlation the importance assigned to each single item rating can be adapted by using item dependent weights. In CF, the item ratings used to make a prediction play the role of features in classical instance-based learning. This paper focuses on item weighting and item selec...

Geographical location is vital to geospatial applications like local search and event detection. In this paper, we investigate and improve on the task of text-based geolocation prediction of Twitter users. Previous studies on this topic have typically assumed that geographical references (e.g., gazetteer terms, dialectal words) in a text are indicative of its author’s location. However, these r...

Designing a robot?s behavior in imprecise, uncertain, dynamic, unpredictable and real-time response domains is very challenging, and even more if an adversarial component is also present. An example of such domains is the robot soccer. In this work we propose the use of Case-Based Reasoning techniques to handle all these features in the action selection problem of a team of robots. Moreover, we...

Performance Analysis of GWAP We started by studying the properties of GWAP (Games With A Purpose) systems and identified the need for proper puzzle selection strategies in order to collect human intelligence in an efficient manner. Based on our analysis, we have proposed the Optimal Puzzle Selection Strategy (OPSA) [3, 7] to improve the efficiency of GWAP systems. Using a comprehensive set of s...