Olivier Teytaud

artificial intelligence evolutionary algorithms games game of go power systems black-box optimization mcts monte-carlo tree search uct upper confidence tree deep networks noisy optimization optimization open source parallel optimization partial observation energy management fully parallel optimization energy transition intelligence artificielle monte carlo tree search simulation-based optimization direct policy search killall-go quasi-random numbers bandits comparison-based optimization minesweeper exp3 nash equilibria parallelism computational complexity derivative free optimization undecidability unit commitment random search tuning hyperparameter search hyperparameter tuning numerical optimization particle swarm optimization differential evolution bayesian optimization game of havannah game of hex alpha-zero deep learning zero learning alphazero computer vision environment water hydroelectricity reinforcement learning wald criterion uncertainty savage criterion bias correction bootstrap jackknife open data investments public continuous non-linear optimization apprentissage automatique vision artificielle réseaux neuronaux profonds evolution strategies uncertainties monte carlo tree search;upper confidence trees planning;power systems réseau éléctrique;centrales électriques électricité;centrales de production;réseau de t statistics;101 fuzzy control go;ai;portfolio;random seeds vc-dimension dynamic programming bandit ucb texp3 metagaming power systems;markov decision processes; optimizat power systems; optimization noisy optimization; simulation-based optimization model predictive control;stochastic dynamic progra computational intelligence operation research; introduction artificial intelligence; games monte-carlo tree seach; subgoal learning; macro-ac sequential decision making games; partial information; artificial intelligenc planning hidden information unstructured optimization simple regrets opening book generation go 7x7 shape game stochastic modelling random positions estimation of distribution algorithms complexity automatic parallelization reweightings weights partially observable game exact solving phantom games variance bias provocative statements energy openoffice linux concurrent version systems svn tao team computer games zermelo algorithm alpha-beta multiobjective optimization expensive optimization multimodal optimization global optimization decidability applications machine learning france functional programming multistage problems bilevel problems cumulative step-size adaptation self-adaptation emna bias and variance evolutionary algorithm very short introduction to direct policy search programming development rules debugging juego del go intelligencia artificial memory in games blind games kriegspiel phantom-go endgames partially observable games batch active learning active learning complexity bounds