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A Stochastic Game Theoretic Differential Dynamic Programming (SGT-DDP) algorithm is derived to solve a differential game under stochastic dynamics. We present the update law for the minimizing and maximizing controls for both players and provide a set of backward differential equations for the second order value function approximation. We compute the extra terms in the backward propagation equations...
Robot social support systems such as robot partner's game interactions with elderly people are very important in ageing societies. Human-robot interaction can decrease the risk of ageing disease such as dementia and thus improve the overall quality of life for the elderly people. However, in order for the robot partner to have successful game interactions with the elderly people, the robot partners...
This paper introduces a strategy planner for nondeterministic hybrid systems with complex continuous dynamics. The planner uses sampling-based techniques and game-theoretic approaches to generate a series of plans and decision choices that increase the chances of success within a fixed time budget. The planning algorithm consists of two phases: exploration and strategy improvement. During the exploration...
In the recent decades an impressive progress was done in automation and robotic fields. Projects such as Google driverless car with “sense and avoid” capabilities or intelligent Unmanned Air Vehicle (UAV) are examples of interesting research works targeting a high degree of autonomy. In this context we underline the unavoidable requirement for improving path planning algo-rithms. Indeed, path planning...
This paper proposed a pursuit-evasion algorithm based on the Option method from hierarchical reinforcement learning and applied it into multi-robot pursuit-evasion game in 2D-Dynamic environment. The algorithm efficiency is studied by comparing it with Q-learning. We decompose the complex task with option method, and divide the learning process into two parts: High-level learning and Low-level learning,...
The thesis presented a heterogeneous players strategy using in RoboCup. The strategy used fuzzy evaluation to obtain the evaluation results of all heterogeneous players on various roles, and constructed a fuzzy inference system to dynamically select equal heterogeneous players for various roles. The simulation experiments and competition results show the application is feasible and effective.
Artificial Immune Systems (AIS) have been successfully modeled and implemented in several engineering applications. In this work, a goalkeeper strategy in robot soccer based on Danger Theory is proposed. Danger Theory is a recent immune theory which has not been widely applied so far. The proposed strategy is implemented and evaluated using middle league SIMUROSOT from FIRA. Experiments carried out...
This paper investigates the computational complexity of planning the motion of a body B in 2-D or 3-D space, so as to avoid collision with moving obstacles of known, easily computed, trajectories. Dynamic movement problems are of fundamental importance to robotics, but their computational complexity has not previously been investigated. We provide evidence that the 3-D dynamic movement problem is...
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