We obtain new results regarding the precise average{ case analysis of the main quantities that intervene in algorithms of a broad Euclidean type. We develop a general framework for the analysis of such algorithms, where the average-case complexity of an algorithm is related to the analytic behaviour in the complex plane of the set of elementary transformations determined by the algorithms. The ...

We develop a general framework for the analysis of algorithms of a broad Euclidean type. The average-case complexity of an algorithm is seen to be related to the analytic behaviour in the complex plane of the set of elementary transformations determined by the algorithms. The methods rely on properties of transfer operators suitably adapted from dynamical systems theory. As a consequence, we ob...

We present a computational model of case-based visual problem solving. The Galatea model and the two experimental participants modeled in it show that 1) visual knowledge is sufficient for transfer of some problemsolving procedures, 2) visual knowledge facilitates transfer even when non-visual knowledge might be available, and 3) the successful transfer of strongly-ordered procedures in which n...

Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performance and/or learning on a different (target) task. TL methods are typically complex, and case-based reasoning can support them in multiple ways. We introduce a method for recognizing intent in a source task, and then app...

While similarity and retrieval in case-based reasoning (CBR) have received a lot of attention in the literature, other aspects of CBR, such as case reuse are less understood. Specifically, we focus on one of such, less understood, problems: knowledge transfer. The issue we intend to elucidate can be expressed as follows: what knowledge present in a source case is transferred to a target problem...

Imitation learning is an effective method for interactively teaching a robot learner to complete a task. We address the problem of transfer for robotic agents that learn tasks from demonstrations, where a robot is asked to adapt a learned task to be repeated in a related, but unfamiliar, environment. We take a case-based approach to transfer, where the robot learner stores individual task demon...

In this study an analytical model for open loop pulsating heat pipes (PHPs) is presented. The model predicts the effect of different parameters such as evaporator temperature, length of evaporator, filling ratio, number of turn and tube diameter on PHP's performance. The governing equations in two phase flow including mass, momentum and energy equations are solved for both one dimensional liqu...