Motivated by efficient algorithms for solving combinatorial and discrete instances of the multi-agent pathfinding problem, this report investigates ways to utilize such solutions to solve similar problems in the continuous domain. While a simple discretization of the space which allows the direct application of combinatorial algorithms seems like a straightforward solution, there are additional...

Video game worlds are getting increasingly large and complex. This poses challenges to the game AI for both pathfinding and strategic decisions, not least in realtime strategy games. One way to alleviate the problem is to manually pre-label the game maps with information about regions and critical choke points, which the game AI can then take advantage of. We present a method for automatically ...

The mechanisms that underlie axonal pathfinding of vomeronasal neurons from the vomeronasal organ (VNO) in the periphery to select glomeruli in the accessory olfactory bulb (AOB) are not well understood. Neuropilin-2, a receptor for secreted semaphorins, is expressed in V1R- and V3R-expressing, but not V2R-expressing, postnatal vomeronasal neurons. Analysis of the vomeronasal nerve in neuropili...

Problems that require multiple agents to follow non-interfering paths from their current states to their respective goal states are called cooperative pathfinding problems. We present the first complete algorithm for finding these paths that is sufficiently fast for real-time applications. Furthermore, our algorithm offers a trade-off between running time and solution quality. We then refine ou...

The navigation activity is an every day practice for any human being capable of locomotion. Our objective in this work is to reproduce this crucial human activity inside virtual environments. Putting together the high complexity of a realistic environment such as a city, a big amount of virtual humans and the real-time constraint requires to optimize each aspect of the animation process. In thi...

Cooperative behavior is a desired trait in many fields from computer games to robotics. Yet, achieving cooperative behavior is often difficult, as maintaining shared information about the dynamics of agents in the world can be complex. We focus on the specific task of cooperative pathfinding and introduce a new approach based on the idea of “direction maps” that learns about the movement of age...

Inspired by the seminal paper on ”Model Transformations? Transformation Models!” [1] we will have a fresh look on the evolution of model evolution. Model evolution is more and more seen as part of change management in general with change as first class principle in the whole software product lifecycle. Thus, a descriptive notion of evolution in terms of evolution models is necessary. In this ta...

This study differentiates between probability models that lead to gardenpathing and those that fail to do so in an incremental dependency parser. Models that take into account intermediate parserstates and part-of-speech pairs correctly reflect human preferences in three wellknown cases: Main Verb vs. Reduced Relative ambiguities, Prepositional Phrase Attachment and Subject-Object ambiguities. ...

The Meta-Agent Conflict-Based Search (MA-CBS) is a recently proposed algorithm for the multi-agent path finding problem. The algorithm is an extension of Conflict-Based Search (CBS), which automatically merges conflicting agents into meta-agents if the number of conflicts exceeds a certain threshold. However, the decision to merge agents is made according to an empirically chosen fixed threshol...