Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical game environments. We describe a parallel implementation of a collaborative diffusion algorithm that is shown to find short paths in real-time across a range of graph sizes and provide a comparison to the well known Dijkstra...

Optimal solutions for multi-agent pathfinding problems are often too expensive to compute. For this reason, suboptimal approaches have been widely studied in the literature. Specifically, in recent years a number of efficient suboptimal algorithms that are complete for certain subclasses have been proposed at highly-rated robotics and AI conferences. However, it turns out that the problem of no...

Collision avoidance is an important topic in multi-robot systems. Existing multi-robot pathfinding approaches ignore sideswipe collisions among robots (i.e., only consider the collision which two agents try to occupy the same node during the same time-step) [1, 3, 4], and allow diagonal move between two adjacent nodes (e.g., Figure 1(b)). However, in many real world applications, sideswipe coll...

Cooperative pathfinding is often addressed in one of two ways in the literature. In fully coupled approaches, robots are considered together and the plans for all robots are constructed simultaneously. In decoupled approaches, the plans are constructed only for a subset of robots at a time. While decoupled approaches can be much faster than fully coupled approaches, they are often suboptimal an...

This paper reports on a project to evaluate the effectiveness of using a Serious Game as a learning tool. A “serious game” has an explicit and carefully thought-out educational purpose and is not intended to be played primarily for amusement. The formal experimental method was designed to compare formal learning of the A* pathfinding algorithm with a digital serious game implementation that uti...

This paper presents a way to dynamically influence the shape and movements of a simulated crowd. We propose a tool and system that allows to modify a crowd’s dynamics in an intuitive, semantically rich and out of context fashion, while being independent from the global path finding architecture and having a low computational cost. We follow a mixed approach where user-specified navigation field...

We use data from a study of finding paths through three different graph depictions: node-link, centered matrix, and quilts to explore how time to solve is influenced by the graph structure: number of nodes, links, skips or layers. We use regressions to determine the influence of these attributes on pathfinding time across depictions. Furthering this idea, we begin to explore how individual user...

different species and neuron types. Some are candi-† Neuron dates for being direct regulators of the molecules that Cell Press confer pathfinding specificity. In each system dis-Cambridge, Massachusetts 02138 cussed, the projection phenotypes of the neurons involved had been described previously so that alterations in pathfinding were easily recognized. Neuronal differentiation has been postula...

First-order learning systems (e.g., FOIL, FOCL, FORTE) generally rely on hill-climbing heuristics in order to avoid the combinatorial explosion inherent in learning first-order concepts. However, hill-climbing leaves these systems vulnerable to local maxima and local plateaus. We present a method, called relational pathfinding, which has proven highly effective in escaping local maxima and cros...

High-quality motion planning can be quite expensive to perform, yet is critical for many video games. As a result, many approximations are employed to reduce costs. Common approximations include pathfinding on a grid or on a navigation mesh instead of in a real-valued world. As a result, the paths that are found are not immediately appropriate for use, and often require post-processing, such as...