Search Algorithms

This module takes a closer look at the links between Artificial Intelligence and the algorithmic complexity of decision and solution search problems. It introduces the concepts of heuristics for games and state graph search, as well as optimization approaches using meta-heuristics. SAT, constraint programming and answer set programming are used to discover declarative and modeling-based approaches.The courses are put into practice with the help of practical exercises in Python.Course outline :Advanced game algorithms (3h / 6h)Heuristics, Alpha-Beta, Iterative DeepeningAlgos on null windowsMonte Carlo Tree SearchPrinciples of Deep Reinforcement Learning for game treesSearching state graphs (2h / 3h)Heuristics, A*Local searchMeta-heuristic search (1h / 3h)Ant colony optimizationGenetic algorithmsSAT and Constraint Programming (3h / 3h)Answer Sets Programming (4h / 6h)Reference book : Artificial Intelligence, a modern approach (Stuart and Russell)

This module takes a closer look at the links between Artificial Intelligence and the algorithmic complexity of decision and solution search problems. It introduces the concepts of heuristics for games and state graph search, as well as optimization approaches using meta-heuristics. SAT, constraint programming and answer set programming are used to discover declarative and modeling-based approaches.The courses are put into practice with the help of practical exercises in Python.Course outline :Advanced game algorithms (3h / 6h)Heuristics, Alpha-Beta, Iterative DeepeningAlgos on null windowsMonte Carlo Tree SearchPrinciples of Deep Reinforcement Learning for game treesSearching state graphs (2h / 3h)Heuristics, A*Local searchMeta-heuristic search (1h / 3h)Ant colony optimizationGenetic algorithmsSAT and Constraint Programming (3h / 3h)Answer Sets Programming (4h / 6h)Reference book : Artificial Intelligence, a modern approach (Stuart and Russell)

This module takes a closer look at the links between Artificial Intelligence and the algorithmic complexity of decision and solution search problems. It introduces the concepts of heuristics for games and state graph search, as well as optimization approaches using meta-heuristics. SAT, constraint programming and answer set programming are used to discover declarative and modeling-based approaches.