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In this paper, a group of mobile robots learns to solve a target reaching problem in a simulated grid environment filled with obstacles. Each robot knows its distance to the target and can communicate with each other. The proposed learning algorithm combines a reinforcement learning algorithm and a swarm optimization algorithm. Q-learning, which is a reinforcement learning algorithm, is modified to...
This paper combines Arithmetic Coding Differential Evolution (ACDE) with Tabu Search. ACDE is a population based binary optimization algorithm. Tabu Search is a local search algorithm. The proposed algorithm can solve very difficult problems reliably and quickly. From the experiment, it can always find an optimum solution for 120-bit Trap, 256-bit HIFF, and 243-bit hTrap in 23, 369, and 60 milliseconds...
Estimation of Distribution Algorithm (EDA) is a new kind of evolutionary algorithm. However, it does not use evolutionary operators such as crossover and mutation. in this paper, we investigate how mutation has an effect on the performance of EDA, more specifically, compact genetic algorithm (cGA) and LZWcGA, the latter uses compressed encoding. the result shows that cGA performs poorly with mutation...
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