As financial products have grown in complexity and level of risk compounding in recent years, investors have come to find it difficult to assess investment risk. Furthermore, companies managing mutual funds are increasingly expected to perform risk control and thus prevent assumption of unforeseen risk by investors. A related revision to the investment fund legal system in Japan led to establishing what is known as “the rule for investment diversification” in December 2014, without a clear discussion of its expected effects on market price formation having taken place. In this paper, we therefore used an artificial market to investigate its effects on price formation in financial markets where investors follow the rule at the time of a market crash that is caused by the collapse of an asset fundamental price. As results, we found the possibility that when the fundamental price of one asset collapses and its market price also collapses, some asset market prices also fall, whereas other asset market prices rise for a market in which investors follow the rule for investment diversification.

The turn of the century is witnessing radical changes in the way information services are spreading due to the progress of IT and the constantly increase in the number of users of the WWW. Therefore, the business market is changing its strategy for a modern online business environment. Autonomous Decentralized Database System (ADDS), based on autonomous coordinating subsystems, has been proposed as a system architecture in order to meet the innovative e-business requirements for consistency and high response among distributed database systems. Autonomy and decentralization of subsystems help achieving high response time in highly competitive situation and autonomous Mobile Agent based coordination has been proposed to achieve flexibility in a highly dynamic environment. In this paper, it is analyzed the case in which the system size increases; and a multi agent coordination, the same number of mobile agents and sites coexist in the system, is proposed for achieving the timeliness property. The response time in the system is conformed by those transactions that require coordination and those that can be satisfied immediately. In accordance, the distribution of the data in the system for coordination is a medullar issue for the improvement of the response time. A trade-off exits between these two kind of transactions depending on the coordination of the Mobile Agents, the capacity of allocating data among the sites, and as well as the distribution of the data and user requests in the system. In this sense, since the system requires high response time, a data allocation technology in which each mobile agent autonomously determine its own capacity for adjusting data among the sites is proposed. Thus, the system will adapt itself to the dynamic environment. The effectiveness of the proposed architecture and technologies are evaluated by simulation.

This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for Autonomous Transportation Systems (ATSs) in manufacturing systems. The TARP is a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW). In our former study, a cooperative algorithm, called the triple loop method, with autonomous distributed agents has been proposed. The Improving initial Task Assignment and Avoiding Deadlock method (ITAAD) is a faster algorithm than the triple loop method. In this paper, we propose a new vehicle routing method for the ITAAD. Results of computational experiments show effectiveness of the proposed routing method.

This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for Autonomous Transportation Systems (ATSs) in manufacturing systems. The TARP results in a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW). As an approach to this problem, a cooperative algorithm with autonomous distributed agents has been proposed. The algorithm is able to plan deadlock-free routes even though the buffer capacity is less, but includes reformability at the point that computation time of that case increases drastically. This paper proposes an initial task assignment method to reduce computation time on planning routes. Results of computational experiments show effectiveness of the proposed method.

Recently, there are so many researches on Autonomous Distributed Manufacturing Systems (ADMSs), where cooperation among agents is used to solve problems, such as the scheduling problem and the vehicle routing problem. We target ADMSs where an ADMS consists of two sub-systems: a Production System (PS) and an Autonomous Transportation System (ATS). This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for ATSs under conditions of given production schedule and finite buffer capacity. The TARP results in a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW), and this paper gives a mathematical formulation of the problem. This paper, also, proposes a cooperative algorithm to obtain suboptimal solutions in which no deadlocks and buffer overflows occur. By computational experiments, we will examine the effectiveness of the proposed algorithm. Computational experiments show that the proposed algorithm is able to obtain efficient and deadlock-free routes even though the buffer capacity is less.

Autonomous distributed manufacturing systems(ADMS) consist of multiple intelligent components with each component acting according to its own judgments. The ADMS objective is to realize more agile and adaptive manufacturing systems. This paper presents the introduction of context-dependent agents (CDAs) in ADMS, and switch strategies depending on system conditions to achieve better performance can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the present paper recalls a basic CDA architecture, and presents the results of an extensive empirical evaluation its performance relative to other rule-based schemes based on several common indices for real-time dispatch.

The present paper addresses the design of manufacturing systems. A resource planning and task allocation problem is proposed, and a multi-agent system for this problem is discussed. In the multi-agent system, an agent exists for each resource and for each operation. The proposed multi-agent system improves the quality of resulting plans by the learning of these agents.