The neural cell adhesion molecule L1 is a member of the immunoglobulin superfamily and it mediates many adhesive interactions during brain development. Mutations in the L1 gene are associated with a spectrum of X-linked neurological disorders known as CRASH or L1 syndrome. The objective of this thesis was to use the zebrafish model to investigate the molecular mechanisms of L1 functions and the pathological effects of its mutations. Zebrafish has two L1 homologs, L1.1 and L1.2. Inhibition of L1.1 expression by antisense morpholino oligonucleotides resulted in phenotypes that showed resemblances to L1 patients. However, knockdown of L1.2 expression did not result in notable neural defects. Furthermore, analysis of the expression pattern of L1.1 has led to the discovery of a novel soluble L1.1 isoform, L1.1s. L1.1s is an alternatively spliced form of L1.1, consisting of the first four Ig-like domains and thus a soluble secreted protein. L1.1 morphants exhibited disorganized brain structures with many having an enlarged fourth/hindbrain ventricle. Further characterization revealed aberrations in ventricular polarity, cell patterning and proliferation and helped differentiate the functions of L1.1 and L1.1s. While L1.1 plays a pivotal role in axonal outgrowth and guidance, L1.1s is crucial to brain ventricle formation. Significantly, L1.1s mRNA rescued many anomalies in the morphant brain, but not the trunk phenotypes. Receptor analysis confirmed that L1.1 undergoes heterophilic interactions with neuropilin-1a (Nrp1a). Peptide inhibition studies demonstrated further the involvement of L1.1s in neuroepithelial cell migration during ventricle formation. In the spinal cord, spinal primary motoneurons expressed exclusively the full-length L1.1, and abnormalities in axonal projections of morphants could be rescued only by L1.1 mRNA. Further studies showed that a novel interaction between the Ig3 domain of L1.1 and Unplugged, the zebrafish muscle specific kinase (MuSK), is crucial to motor axonal growth. Together, these results demonstrate that the different parts of L1.1 contribute to the diverse functions of L1.1 in neural development.

In the adult brain, the thalamocortical tract conveys sensory information from the external environment to the cortex. The cortex analyzes and integrates this information and sends neural responses back to the thalamus through the corticothalamic tract. To reach their final target both thalamocortical and corticothalamic axons have to cover long distances during embryogenesis, changing direction several times and passing through different brain territories. The ventral telencephalon plays a major role in the early development of these tracts. At least three main axon guidance mechanisms act in the ventral telencephalon. First, two different populations of pioneer neurons in the lateral ganglionic eminence (LGE) (LGE pioneer neurons) and medial ganglionic eminence (MGE) (MGE pioneer neurons) provide scaffolds which allow growing corticothalamic and thalamocortical axons to cross the pallium sub pallium boundary (PSPB) and the diencephalic telencephalic boundary (DTB), respectively. Second, the ventral telencephalon forms a permissive corridor for thalamic axons by tangential migration of Isl1 and Ebf1 expressing cells from the LGE into the MGE. Finally, thalamortical and corticothalamic axons guide each other once they have met in the ventral telencephalon (“handshake hypothesis”). The Gli3 transcription factor has been shown to be essential for normal early embryonic regionalization of the mammalian forebrain, although roles of Gli3 in later aspects of forebrain development, like the formation of axonal connections, have not been investigated previously. Here, I present the analysis of axonal tract development in the forebrain of the Gli3 hypomorphic mutant mouse Polydactyly Nagoja (Pdn). These animals lack the major axonal commissures of the forebrain: the corpus callosum, the hippocampal commissure, the anterior commissure and the fimbria. In addition, DiI injections and neurofilament (NF) staining showed defects in the formation of the corticothalamic and thalamocortical tracts. Although the Pdn/Pdn cortex forms early coticofugal neurons and their axons, these axons do not penetrate the LGE and instead run along the PSPB. Later in development, although a thick bundle of Pdn/Pdn cortical axons is still observed to project along the PSPB, some Pdn/Pdn cortical axons eventually enter the ventral telencephalon navigating along several abnormal routes until they reach thalamic regions. In contrast, Pdn/Pdn thalamic axons penetrate into the ventral telencephalon at early stages of thalamic tract development. However, rostrally they deviate from their normal trajectory, leaving the internal capsule prematurely and only few of them reach the developing cortex. Caudally, an ectopic Pdn/Pdn dorsal thalamic axon tract projects ventrally in the ventral telencephalon not entering the internal capsule at all. These defects are still observed in newborn Pdn/Pdn mutant mice. Next, I investigated the developmental mechanisms causing these pathfindings defects. No obvious defects are present in Pdn/Pdn cortical laminae formation and in the patterning of the Pdn/Pdn dorsal thalamus. In addition, Pdn/Pdn thalamocortical axons are able to respond to ventral telencephalic guidance cues when transplanted into wild type brain sections. However, these axonal pathfinding defects correlate with patterning defects of the Pdn/Pdn LGE. This region is partially ventralized and displays a reduction in the number of postmitotic neurons in the mantle zone due to an elongated cell cycle length of LGE progenitor cells. Finally, Pdn/Pdn mutant display an upregulation of Shh expression and Shh signalling in the ventral telencephalon. Interestingly, these patterning defects lead to the absence of DiI back-labelled LGE pioneer neurons, which correlates with the failure of corticothalamic axons to penetrate the ventral telencephalon. In addition, ventral telencephalic thalamocortical guidance mistakes happen at the same time of abnormal formation of the corridor cells. Taken together these data reveal a novel role for Gli3 in the formation of ventral telencephalic intermediate cues important for the development of the thalamocortical and corticothalamic connections. Indeed, Pdn animals are the first known mutants with defective development of the LGE pioneer neurons, and their study provides a link between early patterning defects and axon pathfinding in the developing telencephalon.

There is a growing number of virtual agents in today's virtual worlds. This is directly related to the need of coordinating their behavior and movement. In this work we design algorithms to maintain desired formation of agents while moving through difficult terrain. The methods we study should maintain the requirements of the formation as well as traverse along various obstacles. We then use an arbitrary fitness function to compare the performance of these methods on typical scenarios.

Video game characters must almost always be able to travel from point A to point B and this task can be solved in various ways. There exist grid maps, waypoints, mesh navigation and hierarchical techniques to solve this problem. On randomly generated terrain we make use of automatically generated waypoints to solve pathfinding queries. The waypoints are connected by edges to create a waypoint graph and the graph can be used in real time pathfinding for a single agent in a static environment. This is done by finding the vertices of the blocked triangles from the terrain and place a waypoint on each. We make use of the GPU to create the waypoint graph. The waypoints are connected by utilizing a serialized GPU quad tree to find the relevant blocked geometry to do a line-triangle intersection test. If a line between two waypoints do not intersect any blocked geometry the connection is valid and stored. We found out that it is possible to generate a waypoint graph during the startup of the game with acceptable time results, make use of such a graph for real time pathfinding and that players perceive the paths generated by the algorithm as realistic and responsive. Our conclusion is that our solution is well suited for a deterministic environment with agents of the same size.

Pathfinding is critical to virtual simulation applications. One of the most prominent pathfinding challenges is the fast computation of path plans in large and realistic virtual terrain environments. To tackle this problem, this work proposes the exploration of a quadtree structure in the navigation map representation of large real-world virtual terrains. Exploring a hierarchical approach for virtual terrain representation, we detail how a global hierarchical pathfinding algorithm searches for a path in a coarse initial navigation map representation. Then, during execution time, the pathfinding algorithm refines regions of interest in this terrain representation in order to compute paths with a higher quality in areas where a large amount of navigation obstacles is found. The computational time of such hierarchical pathfinding algorithm is systematically measured in different hierarchical and non-hierarchical terrain representation structures that are instantiated in the modeling of a small real-world terrain scenario. Then, similar experiments are developed in a large real-world virtual terrain that is inserted in a real-life simulation system for the development of military tactical training exercises. The results show that the computational time required to generate pathfinding answers can be optimized when the proposed hierarchical pathfinding algorithm along with the easy and reliable implementation of the quadtree-based navigation map representation of the large virtual terrain are explored in the development of simulation systems.

<p>This thesis serves as an introduction to anyone that has an interest in artificial intelligence games and has experience in programming or anyone who knows nothing of computer games but wants to learn about it. The first part will present a brief introduction to AI, then it will give an introduction to games and game programming for someone that has little knowledge about games. This part includes game programming terminology, different game genres and a little history of games. Then there is an introduction of a couple of common techniques used in game AI. The main contribution of this dissertation is in the second part where three techniques that never were properly implemented before 3D games took over the market are introduced and it is explained how they would be done if they were to live up to today’s standards and demands. These are: line of sight, image recognition and pathfinding. These three techniques are used in today’s 3D games so if a 2D game were to be released today the demands on the AI would be much higher then they were ten years ago when 2D games stagnated. The last part is an evaluation of the three discussed topics.</p>

Pathfinding algorithms used in today&rsquo / s computer games consider path length or a similar criterion as the only measure of optimality. However, these games usually involve opposing parties, whose agents can inflict damage on those of the others&rsquo / . Therefore, the shortest path in such games may not always be the safest one. Consequently, a new suboptimal offline path search algorithm that takes the threat sources into consideration was developed, based on the A* algorithm. Given an upper bound value as the tolerable amount of damage for an agent, this algorithm searches for the shortest path from a starting location to a destination that would cause the agent suffer no more damage than the specified maximum. Due to its mentioned behavior, the algorithm is called Limited-Damage A* (LDA*). Performance of LDA* was tested in randomly-generated and hand-crafted fully-observable maze-like square environments with 8-way grid-abstractions against Multiobjective A* (MOA*), which is a complete and optimal algorithm. It was found to perform much faster than MOA* with allowable sub-optimality in path length.

The neural cell adhesion molecule L1 is a member of the immunoglobulin superfamily and it mediates many adhesive interactions during brain development. Mutations in the L1 gene are associated with a spectrum of X-linked neurological disorders known as CRASH or L1 syndrome. The objective of this thesis was to use the zebrafish model to investigate the molecular mechanisms of L1 functions and the pathological effects of its mutations. Zebrafish has two L1 homologs, L1.1 and L1.2. Inhibition of L1.1 expression by antisense morpholino oligonucleotides resulted in phenotypes that showed resemblances to L1 patients. However, knockdown of L1.2 expression did not result in notable neural defects. Furthermore, analysis of the expression pattern of L1.1 has led to the discovery of a novel soluble L1.1 isoform, L1.1s. L1.1s is an alternatively spliced form of L1.1, consisting of the first four Ig-like domains and thus a soluble secreted protein. L1.1 morphants exhibited disorganized brain structures with many having an enlarged fourth/hindbrain ventricle. Further characterization revealed aberrations in ventricular polarity, cell patterning and proliferation and helped differentiate the functions of L1.1 and L1.1s. While L1.1 plays a pivotal role in axonal outgrowth and guidance, L1.1s is crucial to brain ventricle formation. Significantly, L1.1s mRNA rescued many anomalies in the morphant brain, but not the trunk phenotypes. Receptor analysis confirmed that L1.1 undergoes heterophilic interactions with neuropilin-1a (Nrp1a). Peptide inhibition studies demonstrated further the involvement of L1.1s in neuroepithelial cell migration during ventricle formation. In the spinal cord, spinal primary motoneurons expressed exclusively the full-length L1.1, and abnormalities in axonal projections of morphants could be rescued only by L1.1 mRNA. Further studies showed that a novel interaction between the Ig3 domain of L1.1 and Unplugged, the zebrafish muscle specific kinase (MuSK), is crucial to motor axonal growth. Together, these results demonstrate that the different parts of L1.1 contribute to the diverse functions of L1.1 in neural development.

Detta arbete jämför Theta* och en genetisk algoritm för att undersöka ifall en genetisk algoritm ger mer förutsägbara vägar i dynamiska miljöer än en deterministisk sökteknik. Den valda genetiska algoritmen är inte begränsad till vägval till närliggande noder, den nod som är näst i tur kan ligga var som helst i miljön. Theta* valdes för att matcha detta beteende och anses vara en bra representation av en deterministisk sökteknik då den är en vidareutveckling av standarden A*. Resultaten angående förutsägbarheten samlades in genom en enkätundersökning där fyra aspekter efterfrågades i jämförelser mellan Theta* och den genetiska algoritmen: vilken väg är mjukast, vilken väg är rakast, vilken väg är mest direkt, och vilken väg är kortast. Resultaten visade att den genetiska algoritmen presterat 0,6-2,0% bättre än Theta* och anses därför kunna ge mer förutsägbara vägar. Dock krävs mer forskning för att fastställa hur väsentliga de olika kriterierna är för förutsägbarheten. / This work compares Theta* and a genetic algorithm in order to investigate whether a genetic algorithm gives more predictable paths in dynamic environments than a deterministic search algorithm. The chosen genetic algorithm is not restricted to moving to nearby nodes - the next node may be located anywhere in the environment. Theta* was chosen to match this behaviour and is considered to be a good representation of a deterministic search technique as it is based upon the industry standard A*. Results related to the predictability were collected through a survey where four aspects were asked in comparisons between Theta* and the genetic algorithm: which path is smoother, which path is straighter, which path is more direct, and which path is shorter. The results showed that the genetic algorithm performed 0,6-2,0% better than Theta* and is thereby considered to be able to give more predictable paths. There is however a need for further studies in order to establish how important the criteria are for the predictability.

The Ant Colony Optimization and Particle Swarm Optimization are two Swarm Intelligence algorithms often utilized for optimization. Swarm Intelligence relies on agents that possess fragmented knowledge, a concept not often utilized in games. The aim of this study is to research whether there are any benefits to using these Swarm Intelligence algorithms in comparison to standard algorithms such as A* for pathfinding in a game. Games often consist of dynamic environments with mobile agents, as such all experiments were conducted with dynamic destinations. Algorithms were measured on the length of their path and the time taken to calculate that path. The algorithms were implemented with minor modifications to allow them to better function in a grid based environment. The Ant Colony Optimization was modified in regards to how pheromone was distributed in the dynamic environment to better allow the algorithm to path towards a mobile target. Whereas the Particle Swarm Optimization was given set start positions and velocity in order to increase initial search space and modifications to increase particle diversity. The results obtained from the experimentation showcased that the Swarm Intelligence algorithms were capable of performing to great results in terms of calculation speed, they were however not able to obtain the same path optimality as A*. The algorithms' implementation can be improved but show potential to be useful in games.