tailieunhanh - Robot Soccer Part 7

Tham khảo tài liệu 'robot soccer part 7', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Evolving Fuzzy Rules for Goal-Scoring Behaviour in Robot Soccer 143 to higher-level reasoning using concurrent layered learning - a method in which predefined tasks are learned incrementally with the use of a composite fitness function. The player uses a hand-coded decision tree to make decisions with the leaves of the tree being the learned skills. Whiteson et al. Whiteson Kohl et al. 2003 Whiteson Kohl et al. 2005 study three different methods for learning the sub-tasks of a decomposed task in order to examine the impact of injecting human expert knowledge into the algorithm with respect to the trade-off between making an otherwise unlearnable task learnable the expert knowledge constraining the hypothesis space the effort required to inject the human knowledge. Coevolution layered learning and concurrent layered learning are applied to two versions of keepaway soccer that differ in the difficulty of learning. Whiteson et al. conclude that given a suitable task decomposition an evolutionary-based algorithm in this case neuroevolution can master difficult tasks. They also conclude somewhat unsurprisingly that the appropriate level of human expert knowledge injected and therefore the level of constraint depends critically on the difficulty of the problem. Castillo et al. Castillo Lurgi et al. 2003 modified an existing RoboCupSoccer team - the 11Monkeys team Kinoshita and Yamamoto 2000 - replacing its offensive hand-coded state dependent rules with an XCS genetic classifier system. Each rule was translated into a genetic classifier and then each classifier evolved in real time. Castillo et al. reported that their XCS classifier system outperformed the original 11Monkeys team though did not perform quite so well against other more recently developed teams. In Nakashima Takatani et al. 2004 Nakashima et al. describe a method for learning certain strategies in the RoboCupSoccer environment and report some limited success. The method uses an evolutionary algorithm .