The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The following topic are dealt with: multi-agent reinforcement learning; particle swarm optimisation; fuzzy set theory; collaborative intrusion detection; multimedia processing; chaos synchronization; and genetic algorithm.
Realization of cooperative behavior in multi-agent system is important for improving problem solving ability. Reinforcement learning is one of the learning methods for such cooperative behavior of agents. In this paper, we consider pursuit problem for multi-agent reinforcement learning with communication between the agents. In our study, the agents obtain communication codes through learning. Here,...
The reinforcement learning is applied to automatic parking problem for four-wheeled automobile. The automobile controlled by reinforcement learning learns the appropriate steering angle against the outer environment using distance measuring sensors. The Rational Policy Making (PRM) Method is introduced in order to cope with random start positions. The present method has the advantage of easy implementation...
The assembly process used by most manufacturers today is based on disconnected ordering, scheduling as well as execution processes, and lacks on agility needed for enterprise-wide integration. This paper presents a knowledge-based multi-agent framework to enhance the agility in assembly systems. Agents with specialized expertise and high level of autonomy cooperate together to accomplish individual,...
Real-time reinforcement learning is difficult because number of episodes is too much to complete learning within limited time in practice. On the other hand, in spite of trial-and-error learning, animals can complete learning within limited time. Conventional framework cannot explain it. In this paper, we address the pursuit problem using optical information tau and information of direction that is...
This paper proposes a hybrid approach incorporating an enhanced Nelder-Mead simplex search scheme into a particle swarm optimization (PSO) with the use of a center particle in a swarm for effectively solving multi-dimensional optimization problems. Because of the strength of PSO in performing exploration search and NM simplex search in exploitation search, in addition to the help of a center particle...
In this paper, a novel design approach based on time-response resemblance of the closed-loop system via particle swarm optimization is proposed to improve performance of the redesigned digital system for continuous-time uncertain interval systems. The design rationale of the proposed approach is to derive a digital controller for the redesigned digital system so that step response sequences corresponding...
This investigation introduced a particle swarm optimization (PSO) approach to solve the multi-processor resource-constrained scheduling problems. There are two new rules are proposed and evaluated, named anti-inertia solution generation rule and bidirectional searching rule of PSO. The anti-inertia solution generation rule enables some jobs with anti-inertia velocity used to decide the start processing...
This paper presents a new approach to solve Boolean matrix multiplication using a bio-inspired evolutionary method with DNA computing. While there are many papers proposing the use of DNA for actual computation, very few of these theories are realized in laboratory experiments and those which are successfully implemented are mostly based on protocols introduced in Adleman-Lipton architecture. The...
In our previous paper, we proposed a new classification technique called the Frequency Ratio Accumulation Method (FRAM). This is a simple technique that adds up the ratios of term frequency among categories. However, in FRAM, the use of feature terms is unlimited. In the present paper, we adopt character N-gram as feature terms improving the above-described particularity of FRAM. That is to say, the...
In this paper, we propose a method to generate fictitious user data from a collection of real user data by using confabulation theory. In confabulation theory, the maximum cogent argument for a number of facts is approximated by the maximization of the product of all single-fact cogencies. It has been argued that this approximation is reasonable in cognition. Here, we use this method to generate new...
This paper aims at the construction of a cooperative partner system that plays a seven-card stud poker game with a human partner against an opponent player. If a human player needs some advice on a game, the partner system gives a human partner player strategy to take in a game and its grounds. A human player can also ask some questions about the current situation of a game. If a human player tries...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.