arXiv:1407.0698
Continuous On-line Evolution of Agent Behaviours with Cartesian Genetic Programming
원문 초록
Evolutionary Computation has been successfully used to synthesise controllers for embodied agents and multi-agent systems in general. Notwithstanding this, continuous on-line adaptation by the means of evolutionary algorithms is still under-explored, especially outside the evolutionary robotics domain. In this paper, we present an on-line evolutionary programming algorithm that searches in the agent design space for the appropriate behavioural policies to cope with the underlying environment. We discuss the current problems of continuous agent adaptation, present our on-line evolution testbed for evolutionary simulation.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback
Benchmarking MOEAs for solving continuous multi-objective RL problems
Mergenetic: a Simple Evolutionary Model Merging Library
Evolutionary thoughts: integration of large language models and evolutionary algorithms
RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search
토론
이 논문과 연결된 포럼 글이 아직 없습니다.