Abstract-This article presentsa new algorithm called GPMORL, “Generalised Probabilistic Multi Objective Reinforcement Learning”applied in target search.Probabilisticmethod allows the program to take in count uncertainty with stochastic values which is more than useful. Todiscretize more complex problem, scalarisation isused to combine several objective which droveto perform better.Main reinforcement learning such as Q-Learning and Dynamic Programming are explicitly applied to our application which is rescue and search with a drone.Finally, we demonstrate that the GPMORL can combine both assets of the different previous algorithms. Doing so, stability and convergence speed are improved significantly. Index Terms –Reinforcement Learning, SARSA, Prediction, Control, Q-learning,Gradient Descent, Temporal Difference error, Deterministic, Stochastic, Scalarisation, Multi-Objective, Dynamic Programming, Markov Decision Process Generalised Probabilistic Multi Objective Reinforcement Learning | Request PDF. Available from: https://www.researchgate.net/publication/309314207_Generalised_Probabilistic_Multi_Objective_Reinforcement_Learning [accessed Sep 29 2018] .

Abstract-People always care about their safety. Every government want to protect their citizens. But technology will partially resolve it. Indeed during the next decade self-driving cars will come to mass market. For that cars haveto followan itinerary while behavingsafely in any environment. Consequently, we investigate a mobile robotwhich could represent a self-driving car. This robot must be able to track someone while avoiding obstacles. It can also wandering around to potentially find someone to track. We have focused our work on a threshold logic unit to differentiate each behavior of our robot.In fact, we design this entire mechatronic system. We started to design the electronic design. Then we designed a three wheeled platform. Finally we implementedasimple artificial intelligenceand we tested our tracking by a T-Test. Embedded Mobile Robot: TLU and Image recognition for safe tracking. | Request PDF. Available from: https://www.researchgate.net/publication/309314844_Embedded_Mobile_Robot_TLU_and_Image_recognition_for_safe_tracking [accessed Sep 29 2018].