Ants lay pheromone trails to lead other individuals to a destination. Due to stochastic variations in path following, these paths become optimized. Aspects of this behavior were considered using a simulation modeled on a physical robot colony. Milling and path optimization were observed. This led

Abstract. In this paper we present an experimental setup to model the pheromone trail based foraging behaviour of ants using a special phosphorescent glowing paint. We have built two custom addons for the e-puck robot that allow for trail laying and following on the glowing floor, as well as a way

Ants lay pheromone trails to lead other individuals to a destination. Due to stochastic variations in path following, these paths become optimized. Aspects of this behavior were considered using a simulation modeled on a physical robot colony. Milling and path optimization were observed. This led

has been done on evolutionary multi-objective (EMO) algorithms with probabilistic representation. In this paper, we investigate the performance of two state-of-the-art EMO algorithms-MOEA/D and NSGA-II, with probabilistic representation based on pheromone trails, on the multi-objective travelling

pheromone trails for balanced and dependable

This paper proposes using the rich visual “language ” of Hägerstrand’s time geography to represent time-space relationships in sport, in particular within the spatial and temporal constraints of a game of rugby. Despite being applied outside of its traditional social context it is argued that time geography’s ability to model movements and relationships at the individual level makes it (and its modelling constructs such as prisms and lifelines) a powerful visualisation tool able to provide valuable insights into goal-oriented team sport. The visual tools of time geography are shown in the context of a video information system, SCRUM (Spatio-Chronological Rugby Union Model). 1.

Query Localization is a recently proposed extension for On-Demand Routing Protocols which reduces overheads of route discovery by restricting the query flood to the vicinity of previously discovered routes. In order to effectively define the request zone in Query Localization, the past connectivity information needs to be utilized to the fullest extent. In this paper we propose a swarm intelligence inspired query localization mechanism which tries to effectively harvest the connectivity information gleaned from previous route discoveries in on-demand routing protocols to restrict query flooding.

Query Localization is a recently proposed extension for On-Demand Routing Protocols which reduces overheads of route discovery by restricting the query flood to the vicinity of previously discovered routes. In order to effectively define the request zone in Query Localization, the past connectivity information needs to be utilized to the fullest extent. In this paper we propose a swarm intelligence inspired query localization mechanism which tries to effectively harvest the connectivity information gleaned from previous route discoveries in on-demand routing protocols to restrict query flooding.

Pros and cons of group living in the forest tent caterpillar: separating the roles of silk and of grouping

2 The paper presents an ACO Based Pheromone Trail Evaporation method for fault searching in Power Distribution Networks.ACO Based Pheromone Trail Evaporation method is ‘co-operative agent approach’, which is inspired by the convergence rate and behavior of real ant colonies for finding a shortest