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In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial Ants stand for multi-agent methods inspired by the behavior of real ants.  

In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial Ants stand for multi-agent methods inspired by the behavior of real ants.  

在计算机科学和运筹学中，<font color="#ff8000"> 蚁群优化算法 ant colony optimization algorithm</font>(ACO)是一种解决计算问题的<font color="#ff8000">概率</font>化方法，它可以简化为通过<font color="#ff8000">图</font>来寻找最优路径。人工蚁群代表了受真实蚂蚁行为启发的多主体方法。

在计算机科学和运筹学中，<font color="#ff8000"> 蚁群优化算法 ant colony optimization algorithm</font>(ACO)是一种解决计算问题的<font color="#ff8000">概率 probabilistic</font>化方法，它可以简化为通过<font color="#ff8000">图 Graph (discrete mathematics)</font>来寻找最优路径。人工蚁群代表了受真实蚂蚁行为启发的多主体方法。

The pheromone-based communication of biological [[ant]]s is often the predominant paradigm used.<ref>{{cite book |last = Monmarché Nicolas, Guinand Frédéric and Siarry Patrick  |title = Artificial Ants |publisher = Wiley-ISTE  |year = 2010 |isbn = 978-1-84821-194-0}}</ref>  Combinations of Artificial Ants and [[local search (optimization)|local search]] algorithms have become a method of choice for numerous optimization tasks involving some sort of [[Graph (discrete mathematics)|graph]], e.g., [[vehicle routing problem|vehicle routing]] and internet [[routing]]. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as [[AntOptima]].

The pheromone-based communication of biological [[ant]]s is often the predominant paradigm used.<ref>{{cite book |last = Monmarché Nicolas, Guinand Frédéric and Siarry Patrick  |title = Artificial Ants |publisher = Wiley-ISTE  |year = 2010 |isbn = 978-1-84821-194-0}}</ref>  Combinations of Artificial Ants and [[local search (optimization)|local search]] algorithms have become a method of choice for numerous optimization tasks involving some sort of [[Graph (discrete mathematics)|graph]], e.g., [[vehicle routing problem|vehicle routing]] and internet [[routing]]. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as [[AntOptima]].

The pheromone-based communication of biological ants is often the predominant paradigm used.  Combinations of Artificial Ants and local search algorithms have become a method of choice for numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as AntOptima.

The pheromone-based communication of biological ants is often the predominant paradigm used.  Combinations of Artificial Ants and local search algorithms have become a method of choice for numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. The burgeoning activity in this field has led to conferences dedicated solely to Artificial Ants, and to numerous commercial applications by specialized companies such as AntOptima.

基于信息素的蚂蚁通信方法常被作为一种典型范式<ref>{{cite book |last = Monmarché Nicolas, Guinand Frédéric and Siarry Patrick  |title = Artificial Ants |publisher = Wiley-ISTE  |year = 2010 |isbn = 978-1-84821-194-0}}</ref>。人工蚁群和局部搜索算法的组合已经是许多优化任务的一种求解方法，这些优化任务往往涉及某种<font color="#ff8000">图</font>，例如<font color="#ff8000">车辆路径</font>和<font color="#ff8000">互联网</font>路由的问题。这一领域的蓬勃发展催生了专门讨论人工蚂蚁的学术会议，以及诸如 AntOptima 等专业公司的大量商业应用。

基于信息素的蚂蚁通信方法常被作为一种典型范式<ref>{{cite book |last = Monmarché Nicolas, Guinand Frédéric and Siarry Patrick  |title = Artificial Ants |publisher = Wiley-ISTE  |year = 2010 |isbn = 978-1-84821-194-0}}</ref>。人工蚁群和局部搜索算法的组合已经是许多优化任务的一种求解方法，这些优化任务往往涉及某种，例如<font color="#ff8000">车辆路径 vehicle routing</font>和<font color="#ff8000">互联网路由 internet routing</font>的问题。这一领域的蓬勃发展催生了专门讨论人工蚂蚁的学术会议，以及诸如 AntOptima 等专业公司的大量商业应用。