Detection of tool breakage is very important for automated machining operations. This paper presents a negative-selection algorithm for tool breakage detection. The method is inspired by the defense mechanism of the immune system, which discriminates between self and non-self. Here self is deened to be normal cutting operations and non-self is any deviation beyond allowable variation of the cut...

In this paper we present randomized algorithms for selection on the hypercube. We identify two variants of the hypercube namely, the sequential model and the parallel model. In the sequential model, any node at any time can handle only communication along a single incident edge, whereas in the parallel model a node can communicate along all its incident edges at the same time. We specify three ...

Since testing is an expensive process, test selection has been proposed as a way to reduce such expense. A good selection of tests can be done using specification coverage functions. Model-based ioco theory, however, uses test suites which are not suitable for computing coverage because of interdependence of their test cases. We define a new test suite that overcomes such problems. Using such a...

For single-target tracking problem Kernel-based method has been proved to be effective. A tracker which takes advantage of contextual information to incorporate general constraints on the shape and motion of objects will usually perform better when compare to the one that does not exploit this information. This is due to the reason that a tracker designed to give the best average performance in...

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...

A crucial skill for fluent action meshing in human team activity is a learned and calculated selection of anticipatory actions. We believe that the same holds for robotic teammates, if they are to perform in a similarly fluent manner with their human counterparts. In this work we describe a model for human robot joint action, and propose an adaptive action selection mechanism for a robotic team...

Detection of tool breakage is very important for automated machining operations. This paper presents a negative-selection algorithm for tool breakage detection. The method is inspired by the defense mechanism of the immune system, which discriminates between self and non-self. Here self is deened to be normal cutting operations and non-self is any deviation beyond allowable variation of the cut...

in the software development process, testing is one of the most human intensive steps. many researchers try to automate test case generation to reduce the manual labor of this step. negative selection is a famous algorithm in the field of artificial immune system (ais) and many different applications has been developed using its idea. in this paper we have designed a new algorithm based on nega...

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...

Designing coordinated robot behaviors in uncertain, dynamic, real-time, adversarial environments, such as in robot soccer, is very challenging. In this work we present a case-based reasoning approach for cooperative action selection, which relies on the storage, retrieval, and adaptation of example cases. We focus on cases of coordinated attacking passes between robots in the presence of the de...