Drawing Clustered Graphs - School of Information Technologies
... Academic delegate: “Well, planarity is a central concept even for non-planar graphs. To be able to draw general graphs, we find a topology with a small number of edge crossings, model this topology as a planar graph, and draw that planar graph.” Industry delegate: “Sounds good. But I don’t know how ...
... Academic delegate: “Well, planarity is a central concept even for non-planar graphs. To be able to draw general graphs, we find a topology with a small number of edge crossings, model this topology as a planar graph, and draw that planar graph.” Industry delegate: “Sounds good. But I don’t know how ...
A brief history - School of Information Technologies
... Academic delegate: “Well, planarity is a central concept even for non-planar graphs. To be able to draw general graphs, we find a topology with a small number of edge crossings, model this topology as a planar graph, and draw that planar graph.” Industry delegate: “Sounds good. But I don’t know how ...
... Academic delegate: “Well, planarity is a central concept even for non-planar graphs. To be able to draw general graphs, we find a topology with a small number of edge crossings, model this topology as a planar graph, and draw that planar graph.” Industry delegate: “Sounds good. But I don’t know how ...
Sequencing Operator Counts Toby O. Davies, Adrian R. Pearce, Nir Lipovetzky
... the corresponding operator count does not necessarily represent a valid plan. Our approach can be used both as an incremental lower bound function and as an optimal planner, much like h++ (Haslum 2012), as our approach does not terminate until it finds a proof that it has computed h∗ , i.e. finds a ...
... the corresponding operator count does not necessarily represent a valid plan. Our approach can be used both as an incremental lower bound function and as an optimal planner, much like h++ (Haslum 2012), as our approach does not terminate until it finds a proof that it has computed h∗ , i.e. finds a ...
Pdf - Text of NPTEL IIT Video Lectures
... Once, we are getting that then we will. In the next step we will linearise the corresponding g j X prime about X 2. That means, we will get another linear constraint of this. Thus, it will become g j X prime X 2 would be X would be approximately equal to g j X 2 prime X 2 plus grad of g j prime (X ...
... Once, we are getting that then we will. In the next step we will linearise the corresponding g j X prime about X 2. That means, we will get another linear constraint of this. Thus, it will become g j X prime X 2 would be X would be approximately equal to g j X 2 prime X 2 plus grad of g j prime (X ...
The Hardest Random SAT Problems
... very variable problem diculty. There appears to be a \constraint gap" in this region. That is, the unit and pure rules are often unable to identify any constraint on the truth assignments. We are thus forced to use the split rule extensively. This would suggest that the depth of search (i.e. the de ...
... very variable problem diculty. There appears to be a \constraint gap" in this region. That is, the unit and pure rules are often unable to identify any constraint on the truth assignments. We are thus forced to use the split rule extensively. This would suggest that the depth of search (i.e. the de ...
Sequencing Operator Counts
... the corresponding operator count does not necessarily represent a valid plan. Our approach can be used both as an incremental lower bound function and as an optimal planner, much like h++ (Haslum 2012), as our approach does not terminate until it finds a proof that it has computed h∗ , i.e. finds a ...
... the corresponding operator count does not necessarily represent a valid plan. Our approach can be used both as an incremental lower bound function and as an optimal planner, much like h++ (Haslum 2012), as our approach does not terminate until it finds a proof that it has computed h∗ , i.e. finds a ...
Core Node Location Problem - Robert B. Willumstad School of
... Metro networks usually span up to 200 km and serve as an intermediary network between access and backbone networks. Various design/service problems facing metro network administrators and designers include: traffic grooming to use resources more efficiently, subwavelength switching based on GMPLS (g ...
... Metro networks usually span up to 200 km and serve as an intermediary network between access and backbone networks. Various design/service problems facing metro network administrators and designers include: traffic grooming to use resources more efficiently, subwavelength switching based on GMPLS (g ...
Case Adaptation by Segment Replanning for Case
... In a case-based planning domain, a case is a plan and the improvement of the case quality in the STRIPS-version is the reduction of the number of actions that guides the plan from the initial state to the final state. The purpose of an adaptation process applied to a Case-Based planning system is to ...
... In a case-based planning domain, a case is a plan and the improvement of the case quality in the STRIPS-version is the reduction of the number of actions that guides the plan from the initial state to the final state. The purpose of an adaptation process applied to a Case-Based planning system is to ...
mohammad.ghoniem.info
... In this paper, we present a recent technique that uses adjacency matrices instead of node-link diagrams to interactively visualize and explore large graphs, with thousands of nodes and any number of links. This technique relies on the well known property that a graph may be represented by its connec ...
... In this paper, we present a recent technique that uses adjacency matrices instead of node-link diagrams to interactively visualize and explore large graphs, with thousands of nodes and any number of links. This technique relies on the well known property that a graph may be represented by its connec ...
Reinforcement Learning for Neural Networks using Swarm Intelligence
... balance problem. A double CMAC network [22] with one trained for generality and the other trained for accuracy near the target was also applied to the double pole balance problem. The neuroevolutionary method Enforced Subpopulations (ESP) [23] proved effective at solving both the standard and non-Ma ...
... balance problem. A double CMAC network [22] with one trained for generality and the other trained for accuracy near the target was also applied to the double pole balance problem. The neuroevolutionary method Enforced Subpopulations (ESP) [23] proved effective at solving both the standard and non-Ma ...
Time-Memory Trade-Off for Lattice Enumeration in a Ball
... propose a new algorithm for enumerating lattice point in a ball of radius 1.156λ1 (Λ) in time 3n+o(n) , where λ1 (Λ) is the length of the shortest vector in the lattice Λ. Then, we show how this method can be used for solving SVP and the Closest Vector Problem (CVP) with approximation factor γ = 1.9 ...
... propose a new algorithm for enumerating lattice point in a ball of radius 1.156λ1 (Λ) in time 3n+o(n) , where λ1 (Λ) is the length of the shortest vector in the lattice Λ. Then, we show how this method can be used for solving SVP and the Closest Vector Problem (CVP) with approximation factor γ = 1.9 ...
slides
... Other solutions To construct an iMZ , we have to check four constraints : i. Muu = (1 − Zu ) ii. 0 ≤ M u iii. M u ≤ 1 − Z iv. M u ≤ M v for u < v These constraints are easy to handle if M u are solutions of a SDE: The constraint i indicates the initial condition; the constraint ii means that we must ...
... Other solutions To construct an iMZ , we have to check four constraints : i. Muu = (1 − Zu ) ii. 0 ≤ M u iii. M u ≤ 1 − Z iv. M u ≤ M v for u < v These constraints are easy to handle if M u are solutions of a SDE: The constraint i indicates the initial condition; the constraint ii means that we must ...
Travelling salesman problem
The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.TSP is a special case of the travelling purchaser problem and the Vehicle routing problem.In the theory of computational complexity, the decision version of the TSP (where, given a length L, the task is to decide whether the graph has any tour shorter than L) belongs to the class of NP-complete problems. Thus, it is possible that the worst-case running time for any algorithm for the TSP increases superpolynomially (perhaps, specifically, exponentially) with the number of cities.The problem was first formulated in 1930 and is one of the most intensively studied problems in optimization. It is used as a benchmark for many optimization methods. Even though the problem is computationally difficult, a large number of heuristics and exact methods are known, so that some instances with tens of thousands of cities can be solved completely and even problems with millions of cities can be approximated within a small fraction of 1%.The TSP has several applications even in its purest formulation, such as planning, logistics, and the manufacture of microchips. Slightly modified, it appears as a sub-problem in many areas, such as DNA sequencing. In these applications, the concept city represents, for example, customers, soldering points, or DNA fragments, and the concept distance represents travelling times or cost, or a similarity measure between DNA fragments. The TSP also appears in astronomy, as astronomers observing many sources will want to minimise the time spent slewing the telescope between the sources. In many applications, additional constraints such as limited resources or time windows may be imposed.