scholarly journals Theory and Techniques for Synthesizing Efficient Breadth-First Search Algorithms

2012 ◽  
pp. 308-325 ◽  
Author(s):  
Srinivas Nedunuri ◽  
Douglas R. Smith ◽  
William R. Cook
Keyword(s):  
Search Algorithms ◽  
Breadth First Search

An Overview of P2P Search Algorithms

2011 ◽  
Vol 267 ◽  
pp. 393-397 ◽  
Author(s):  
Jing Feng Yan ◽  
Shao Hua Tao
Keyword(s):  
High Performance ◽  
Search Algorithm ◽  
Search Algorithms ◽  
P2p Network ◽  
Breadth First Search ◽  
Research Focus ◽  
Web Based ◽  
Advantages And Disadvantages ◽  
Resource Search ◽  
Research Findings

since the nodes of P2P network always join or exit dynamically, web-based P2P search technology is much more complicated than the traditional search technologies. P2P-based resource search algorithm is currently a research focus. This paper finds the advantages and disadvantages and range of application of each algorithm through an analysis and comparison of methods such as flooding search, breadth-first search (BFS), iterative depth method, directed breadth-first search (DBFS), random breadth-first search (RBFS) and other forwarding mechanism-based search. And the research findings of this paper aims to lay a technically necessary foundation for future high-performance P2P search algorithm.

Partition-Based Hybrid MIMO Decoding Schemes with Combined Depth- and Breath-First Search

2013 ◽  
Vol 284-287 ◽  
pp. 2652-2656
Author(s):  
Jong In Park ◽  
Young Po Lee ◽  
Seok Ho Yoon
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
Multiple Input Multiple Output ◽  
Search Algorithms ◽  
Search Method ◽  
Breadth First Search ◽  
Error Performance ◽  
Search Methods ◽  
Multiple Input ◽  
Input Multiple Output

In this paper, we propose a novel maximum likelihood (ML) decoding scheme based on the combination of depth- and breadth-first search methods on a partitioned tree for multiple input multiple output systems. The proposed scheme first partitions the searching tree into several stages, each of which is then searched by a depth- or breadth-first search method, possibly exploiting the advantages of both the depth- and breadth-first search methods in an organized way. Numerical results indicate that, when the depth- and breadth-first search algorithms are adopted appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance.

scholarly journals Artificial Intelligence based Pacman Game

2020 ◽  
Vol 9 (9) ◽  
pp. 140-144
Keyword(s):  
Artificial Intelligence ◽  
Video Game ◽  
Environmental Conditions ◽  
Search Algorithms ◽  
Breadth First Search ◽  
Artificial Intelligence Research ◽  
Depth First Search ◽  
Optimal Paths ◽  
Alpha Beta ◽  
Multi Agents

This paper is about implementing pacman game with AI.The Game Pac-Man is a very challenging video game that can be useful in conducting AI(Artificial Intelligence) research. Here,the reason we have implemented various AI algorithms for pacman game is that it helps us to study AI by using visualizations through which we can understand AI more ef- fectively.The main aim is to build an intelligent pacman agent which finds optimal paths through the maze to find a particular goal such as a particular food position,escaping from ghosts.For that, we have implemented AI search algorithms like Depth first search,Breadth first search,A*search,Uniform cost search.We have also implemented multi-agents like Reflex agent,Minimax agent,Alpha-beta agent.Through these multiagent algorithms,we can make pacman to react from its environmental conditions and escape from ghosts to get high score.We have also done the visualization part of the above AI algorithms by which anyone can learn and understand AI algorithms easily.For visualisation of algorithms,we have used python libraries matplotlib and Networkx.

scholarly journals Finding Optimal Algorithm in Artificial Intelligence

2021 ◽  
Vol 10 (7) ◽  
pp. 84-90
Author(s):  
I.Parvin Begum ◽  
I.Shahina Begam
Keyword(s):  
Artificial Intelligence ◽  
Shortest Path ◽  
Heuristic Search ◽  
Optimal Algorithm ◽  
Search Algorithms ◽  
Search Procedure ◽  
Breadth First Search ◽  
Search Techniques ◽  
Best First Search ◽  
Blind Search

Present days many artificial intelligence search algorithms are plays a important to figure out the problem of shortest path finding. The paper presents the detailed study of heuristic search and blind search techniques. The paper focus additional in the direction of blind search strategies such as Breadth First Search, Depth First Search, and Uniform Cost Search and informed explore strategies like A*, and Best First Search. The paper consist of effective of search procedure, their qualities, and demerits, where these algorithms are applicable, also at last comparison of search techniques based on complexity, optimality and completeness are presented in tabular structure.

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