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Computer has been widely used and fully researched along with the progress of electronic technology. We are no longer satisfied with simple calculation in computer application, but expect they can replace the human brain to accomplish complex work. So the artificial intelligence has emerged. There is a very classic research topic in the history of artificial intelligence — Intelligent Planning. IJCAI...
This paper proposes a Multiple-run Interactive Certainty Network (MRICN) that integrates human decision-making heuristics into probabilistic approaches for knowledge-based systems. MRICN is built upon ideas drawn from “Opinion Pooling”, “Probabilistic Network” and “Interaction”, allowing for reflective searching for the optimal sets of knowledge with the maximal certainty gain. It is implemented and...
This paper revisits a traditional Ant Foraging algorithm and proposes a Cluster-based Softbots algorithm to address the performance issues caused by constraints of random autonomous search featured in most swarm intelligence-based algorithms. A simple hierarchy is introduced to regulate the unfolding of dynamically changing swarm-like behaviors. Comparative experiments for Ant Foraging and the proposed...
Clustering analysis based on ant swarm intelligence is discussed. As traditional clustering algorithm is easy to obtain local optimum, it uses ant swarm intelligence to obtain global search. It improves the clustering by locating the objects in a cluster with the probability, which is updated by the pheromone, while the rule of updating pheromone is according to total within cluster variance. According...
Particle swarm optimization (PSO) is a heuristic optimization technique that uses previous personal best experience and global best experience to search global optimal solutions. This paper studies the application of PSO techniques to multi-objective optimization using decomposition methods. A new decomposition-based multi-objective PSO algorithm is proposed, called MOPSO/D. It integrates PSO into...
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