Implementasi Algoritma Dijkstra Pada Game Pacman

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 170-176
Author(s):  
Anggit Dwi Hartanto ◽  
Aji Surya Mandala ◽  
Dimas Rio P.L. ◽  
Sidiq Aminudin ◽  
Andika Yudirianto
Keyword(s):  
Artificial Intelligence ◽  
Greedy Algorithm ◽  
Dijkstra Algorithm ◽  
Testing Phase ◽  
A Value ◽  
Route Problem ◽  
Starting Point ◽  
The Greedy Algorithm

Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

Section 5.d Introduction

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Calin GURAU ◽  
Ashok RANCHHOD
Keyword(s):  
Best Practices ◽  
Brand Strategy ◽  
Brand Experience ◽  
Creation Process ◽  
A Value ◽  
Starting Point

 The classic brand design literature presents and illustrates best practices in developing the physical, graphical and semiotic aspects of a brand. However, both practitioners and academics outline that brand design is only the starting point of the brand strategy, which has to be completed and complemented by designing and effectively managing meaningful brand experiences. The success of the brand depends on a value co-creation process in which the intentions and offerings of producers and vendors encounter, and interact with, the customer experiences of the brand and of the associated product. A brand experience designed for the customer can therefore be multi-dimensional and not just product led.

scholarly journals An Optimized Algorithm and Test Bed for Improvement of Efficiency of ESS and Energy Use

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 388 ◽  
Author(s):  
Seung-Mo Je ◽  
Jun-Ho Huh
Keyword(s):  
Greedy Algorithm ◽  
Energy Use ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Test Bed ◽  
C Language ◽  
Improvement Plan ◽  
The Republic ◽  
The Greedy Algorithm

The Republic of Korea (ROK) has four distinct seasons. Such an environment provides many benefits, but also brings some major problems when using new and renewable energies. The rainy season or typhoons in summer become the main causes of inconsistent production rates of these energies, and this would become a fatal weakness in supplying stable power to the industries running continuously, such as the aquaculture industry. This study proposed an improvement plan for the efficiency of Energy Storage System (ESS) and energy use. Use of sodium-ion batteries is suggested to overcome the disadvantages of lithium-ion batteries, which are dominant in the current market; a greedy algorithm and the Floyd–Warshall algorithm were also proposed as a method of scheduling energy use considering the elements that could affect communication output and energy use. Some significant correlations between communication output and energy efficiency have been identified through the OPNET-based simulations. The simulation results showed that the greedy algorithm was more efficient. This algorithm was then implemented with C-language to apply it to the Test Bed developed in the previous study. The results of the Test Bed experiment supported the proposals.

scholarly journals Bands in the secondary spectrum of hydrogen

1927 ◽  
Vol 114 (767) ◽  
pp. 293-313 ◽  
Keyword(s):  
Quantum Theory ◽  
Static Model ◽  
Moment Of Inertia ◽  
Initial Moment ◽  
A Value ◽  
Starting Point ◽  
Band Spectra ◽  
The University ◽  
Low Pressures ◽  
Complete Account

Fulcher’s discovery of bands in the secondary spectrum of hydrogen at low pressures proved the starting point of a number of investigations, including those, based on the valuable tables of Merton and Barratt, which have been carried out in the University of St. Andrews. The application of the quantum theory to these bands has been discussed by one of us (H. S. A.), by Curtis, and in particular by Richardson who, partly in association with Tanaka, has added greatly to the number of known regularities and done much to bring them into line with the theory of band spectra. Nevertheless, apart from the Fulcher system, of which Richardson has recently given a very complete account, there remains a very large number of lines which have not yet been classified. One of the present writers (I. S.) has been engaged in a study of the secondary spectrum at higher pressures, and among the regularities which have been selected by this method is a band with head at 4582·58 A. U. and shading towards the violet, which has been described in a recent communication. This band yielded an initial moment of inertia agreeing closely with a value deduced from a static model of triatomic hydrogen, H 3 . This band has since been found to be one of a large number of similar bands which it will be the purpose of this paper to describe. We shall refer to it for convenience as “Band II A , a .”

scholarly journals Enhanced Particle Swarm Optimization for Effective Relay Nodes Deployment in Wireless Sensor Networks

2021 ◽  
Vol 13 (1) ◽  
pp. 53-73
Author(s):  
Bader Alshaqqawi ◽  
Sardar Anisul Haque ◽  
Mohammed Alreshoodi ◽  
Ibrahim Alsukayti
Keyword(s):  
Wireless Sensor Networks ◽  
Particle Swarm Optimization ◽  
Sensor Networks ◽  
Greedy Algorithm ◽  
Pso Algorithm ◽  
Optimization Process ◽  
Wireless Sensor ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
The Greedy Algorithm

One of the critical design problems in Wireless Sensor Networks (WSNs) is the Relay Node Placement (RNP) problem. Inefficient deployment of RNs would have adverse effects on the overall performance and energy efficiency of WSNs. The RNP problem is a typical example of an NP-hard optimization problem which can be addressed using metaheuristics with multi-objective formulation. In this paper, we aimed to provide an efficient optimization approach considering the unconstrained deployment of energy-harvesting RNs into a pre-established stationary WSN. The optimization was carried out for three different objectives: energy consumption, network coverage, and deployment cost. This was approached using a novel optimization approach based on the integration of the Particle Swarm Optimization (PSO) algorithm and a greedy technique. In the optimization process, the greedy algorithm is an essential component to provide effective guidance during PSO convergence. It supports the PSO algorithm with the required information to efficiently alleviate the complexity of the PSO search space and locate RNs in the spots of critical significance. The evaluation of the proposed greedy-based PSO algorithm was carried out with different WSN scenarios of varying complexity levels. A comparison was established with two PSO variants: the classical PSO and a PSO hybridized with the pattern search optimizer. The experimental results demonstrated the significance of the greedy algorithm in enhancing the optimization process for all the considered PSO variants. The results also showed how the solution quality and time efficiency were considerably improved by the proposed optimization approach. Such improvements were achieved using a simple integration technique without adding to the complexity of the system and introducing additional optimization stages. This was more evident in the RNP scenarios of considerably large search spaces, even with highly complex and challenging setups.

scholarly journals Misconceptions in the health technology industry that are delaying the translation of artificial intelligence technology into relevant clinical applications

2021 ◽  
Vol 54 (4) ◽  
pp. 243-245
Author(s):  
Fabíola Macruz
Keyword(s):  
Artificial Intelligence ◽  
Human Performance ◽  
Health Technology ◽  
Medical Community ◽  
Technology Industry ◽  
Diagnosis And Prognosis ◽  
Starting Point ◽  
Causative Factors ◽  
The Status ◽  
Artificial Intelligence Technology

Abstract There is great optimism that artificial intelligence (AI), as it disrupts the medical world, will provide considerable improvements in all areas of health care, from diagnosis to treatment. In addition, there is considerable evidence that AI algorithms have surpassed human performance in various tasks, such as analyzing medical images, as well as correlating symptoms and biomarkers with the diagnosis and prognosis of diseases. However, the mismatch between the performance of AI-based software and its clinical usefulness is still a major obstacle to its widespread acceptance and use by the medical community. In this article, three fundamental concepts observed in the health technology industry are highlighted as possible causative factors for this gap and might serve as a starting point for further evaluation of the structure of AI companies and of the status quo.

Sign in / Sign up

Export Citation Format

Share Document