One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core of any AI movement system. The two main components for basic real-time pathfinding are (i) travelling towards a specified goal and (ii) avoiding dynamic and static obstacles that may litter the path to this goal. The ...

A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS), the latter is usually associated with the cost surface method, which allows optimum paths to be calculated through rasters in which the value of each cell depicts the co...

Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that each agent reaches its goal and do not collide. In recent years, variants MAPF have risen in a wide range real-world applications as warehouse management autonomous vehicles. Optimizing common objectives, minimizing sum-of-costs or makespan, computationally intractable, but state-of-the-art algorithms a...

Pathfinding on large maps is time-consuming. Classical search algorithms such as Dijkstra’s and A* algorithms may solve difficult problems in polynomial time. However, in real-world pathfinding examples where the search space increases dramatically, these algorithms are not appropriate. Hierarchical pathfinding algorithms that provide abstract plans of future routing, such as HPA* and PRA*, hav...

Rhythmic spontaneous electrical activity occurs in many parts of the developing nervous system, where it plays essential roles in the refinement of neural connections. By blocking or slowing this bursting activity, via in ovo drug applications at precise developmental periods, we show that such activity is also required at much earlier stages for spinal motoneurons to accurately execute their f...

Real-time heuristic search is suitable for time-sensitive pathfinding and planning tasks when an AI-controlled nonplayable character must interleave its planning and plan execution. Since its inception in the early 90s, numerous realtime heuristic search algorithms have been proposed. Many of the algorithms also have control parameters leaving a practitioner with a bewildering array of choices....

Neuronal growth cones navigate over long distances along specific pathways to find their correct targets. The mechanisms and molecules that direct this pathfinding are the topics of this review. Growth cones appear to be guided by at least four different mechanisms: contact attraction, chemoattraction, contact repulsion, and chemorepulsion. Evidence is accumulating that these mechanisms act sim...

In this paper we combine recent pathfinding research on spatial abstractions, partial refinement, and space-time reservations to construct new collaborative pathfinding algorithms. We first present an enhanced version of WHCA* and then show how the ideas from WHCA* can be combined with PRA* to form CPRA*. These algorithms are shown to effectively plan trajectories for many objects simultaneousl...

A multiterminal obstacle-avoiding pathfinding approach is proposed. The inspired by deep image learning. key idea based on training a conditional generative adversarial network (cGAN) to interpret task as graphical bitmap and consequently map onto solution represented another bitmap. To enable the proposed cGAN pathfinding, methodology for generating synthetic dataset also model implemented in ...

Migrating cells and growth cones extend lamellipodial and filopodial protrusions that are required for outgrowth and guidance. The mechanisms of cytoskeletal regulation that underlie cell and growth cone migration are of much interest to developmental biologists. Previous studies have shown that the Arp2/3 complex and UNC-115/abLIM act redundantly to mediate growth cone lamellipodia and filopod...