Bulent Tastan

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The creation of effective autonomous agents (bots) for combat scenarios has long been a goal of the gaming industry. However, a secondary consideration is whether the autonomous bots behave like human players; this is especially important for simulation/training applications which aim to instruct participants in real-world tasks. Bots often compensate for a(More)
One of themost powerful constraints governingmany activity recognition problems is that imposed by the human actor. It is well known that humans have a large set of physical and cognitive limitations that constrain their execution of various tasks. In this article, we show how prior knowledge of these perception and locomotion limitations can be exploited(More)
One important aspect of creating game bots is adversarial motion planning: identifying how to move to counter possible actions made by the adversary. In this paper, we examine the problem of opponent interception, in which the goal of the bot is to reliably apprehend the opponent. We present an algorithm for motion planning that couples planning and(More)
Multi-robot manipulation tasks are challenging for robots to complete in an entirely autonomous way due to the perceptual and cognitive requirements of grasp planning, necessitating the development of specialized user interfaces. Yet even for humans, the task is sufficiently complex that a high level of performance variability exists between a novice and an(More)
A high-quality human-robot interface is essential for the success of search and rescue operations in urban environments that are too challenging for fully-autonomous operation. Teleoperating multiple robots greatly increases the complexity of the human’s cognitive task, since the operator’s concentration is divided among multiple robots. Thus, simply adding(More)
Dynamic service composition is an important challenge for many applications. This paper considers dynamic composition where the parties involved and the process they execute changes based on context. In such a setting, creating compositions from scratch is costly. Instead, we advocate automatic adaptation of existing compositions to fit the requested(More)
The ability to predict the path of a moving human is a crucial element in a wide range of applications, including video surveillance, assisted living environments (smart homes), and simulation environments. Two tasks, tracking (finding the user's current location) and goal prediction (identifying the final destination) are particularly relevant to many(More)
My research is focused on using human navigation data in games and simulation to learn motion models from trajectory data. These motion models can be used to: 1) track the opponent’s movement during periods of network occlusion; 2) learn combat tactics by demonstration; 3) guide the planning process when the goal is to intercept the opponent. A training set(More)
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