Mobile Ad Hoc Networks (MANETs) are networks in which all nodes are mobile and communicate with each other via wireless connections. Nodes can join or leave at anytime. There is no fixed infrastructure, all nodes are equal and there is no centralized control or overview. There are no designated routers: all nodes can serve as routers for each other, and data packets are forwarded from node to node in a multi-hop fashion.Since a few years research interest in MANETs has been growing, and especially the design of MANET routing protocols has received a lot of attention. One of the reasons is that routing in MANETs is a particularly challenging task due to the fact that the topology of the network changes constantly, and paths which were initially efficient can quickly become inefficient or even infeasible. Moreover, control information flow in the network is very restricted. This is because the bandwidth of the wireless medium is limited, and the medium is shared. The access to the shared channel is controlled by protocols at the Medium Access Control layer (MAC), such as ANSI/IEEE 802.11 DCF (which is commonly used in MANETs), which in their turn create extra overhead. It is therefore important to design algorithms that are adaptive, robust and self-healing. Moreover, they should work in a localized way, due to the lack of central control or infrastructure in the network. Here we describe AntHocNet, a new routing algorithm for MANETs. AntHocNet's design is based on a specific self-organizing behavior of ant colonies, the shortest paths discovery, and on the related framework of Ant Colony Optimization (ACO). It has been observed that ants in a colony can converge on moving over the shortest among different paths connecting their nest to a food source. The main catalyst of this colony-level shortest path behavior is the use of a volatile chemical substance called pheromone: ants moving between the nest and a food source deposit pheromone, and preferentially move towards areas of higher pheromone intensity. Shorter paths can be completed quicker and more frequently by the ants, and will therefore be marked with higher pheromone intensity. These paths will then attract more ants, which will in turn increase the pheromone level, until there is convergence of the majority of the ants onto the shortest path. The local intensity of the pheromone field, which is the overall result of the repeated and concurrent path sampling experiences of the ants, encodes a spatially distributed measure of goodness associated with each move. This form of distributed control based on indirect communication among agents which locally modify the environment and react to these modifications leading to a phase of global coordination of the agent actions is called stigmergy .