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 that switch strategies depending on system conditions to achieve better performance than can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the paper presents a basic CDA architecture and the results of an extensive empirical evaluation of its performance relative to other rule-based schemes based on several common indices for real-time dispatch.

For a service-oriented architecture-based system, the problem of synthesizing a concrete model (i.e., behavioral model) for each peer configuring the system from an abstract specification-which is referred to as choreography-is known as the choreography realization problem. A flow of interaction of peers is called a scenario. In our previous study, we showed conditions and an algorithm to synthesize concrete models when choreography is given by one scenario. In this paper, we extend the study for choreography given by two scenarios. We show necessary and sufficient conditions on the realizability of choreography under both cases where there exist conflicts between scenarios and no conflicts exist.

Event structures are a well-known modeling formalism for concurrent systems with causality and conflict relations. The flow event structure (FES) is a variant of event structures, which is a generalization of the prime event structure. In an FES, two events may be in conflict even though they are not syntactically in conflict; this is called a semantic conflict. The existence of semantic conflict in an FES motivates reducing conflict relations (i.e., conflict reduction) to obtain a simpler structure. In this paper, we study conflict reduction in acyclic FESs. A necessary and sufficient condition for conflict reduction is given; algorithms to compute semantic conflict, local configurations, and conflict reduction are proposed. A great time reduction was observed in computational experiments when comparing the proposed with the naive method.

Signal Transition Graphs (STG's) are Petri nets, which were introduced to represent a behavior of asynchronous circuits. To derive logic functions from an STG, the reachability graph should be constructed. In the verification of STG's some method based on an Occurrence net (OCN) and its prefix, called an unfolding, has been proposed. OCN's can represent both causality and concurrency between two nodes by net structure. In this paper, we propose a method to derive a logic function by generating sub state space of a given STG using the structural properties of OCN.

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.

This paper proposes an algorithm for analyzing the reachability property of Petri nets by the use of unfoldings. It is known that analyzing the reachability by using unfoldings requires exponential time and space to the size of unfolding. The algorithm is based on the branch and bound technique, and experimental results show efficiency of the algorithm.

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.

For a service-oriented architecture based system, the problem of synthesizing a concrete model, i.e., behavioral model, for each service configuring the system from an abstract specification, which is referred to as choreography, is known as the choreography realization problem. In this paper, we assume that choreography is given by an acyclic relation. We have already shown that the condition for the behavioral model is given by lower and upper bounds of acyclic relations. Thus, the degree of freedom for behavioral models increases; developing algorithms of synthesizing an intelligible model for users becomes possible. In this paper, we introduce several metrics for intelligibility of state machines, and study the algorithm of synthesizing Pareto efficient state machines.

The present paper discusses an assembly line balancing problem (ALBP). ALBP discussed up to now does not consider rack spaces where tools or parts are stored. We introduce an extended resource planning and assembly line balancing problem that takes the rack space into account. An exact search method for solving the problem by using a graph structure, and a heuristics for the method are proposed. The proposed method is evaluated by computational experiments.

In this paper, we discuss an abstraction method for Petri nets based on an equivalence of firing sequences of a specified subnet or a specified subset of transitions. Specifically, a method is presented to generate an equivalent net which preserves firing sequences of a specified subnet or a specified subset of transitions. The abstraction can be applied to an efficient behavioral analysis of concurrent systems constructed by composition of modules such as communication networks and Flexible Manufacturing Systems (FMS).

In this letter, we present the evaluation of an option-based learning algorithm, developed to perform a conflict-free allocation of calls among cars in a multi-car elevator system. We evaluate its performance in terms of the service time, its flexibility in the task-allocation, and the load balancing.

The choreography realization problem is a design challenge for systems based on service-oriented architecture. In our previous studies, we studied the problem on a case where choreography was given by one or two scenarios and was expressed by an acyclic relation of events; we introduced the notion of re-constructibility as a property of acyclic relations to be satisfied. However, when choreography is defined by multiple scenarios, the resulting behavior cannot be expressed by an acyclic relation. An event structure is composed of an acyclic relation and a conflict relation. Because event structures are a generalization of acyclic relations, a wider class of systems can be expressed by event structures. In this paper, we propose the use of event structures to express choreography, introduce the re-constructibility of event structures, and show a necessary condition for an event structure to be re-constructible.

Petri nets are known as a modeling language for concurrent and distributed systems. In recent years, various object-oriented Petri nets were proposed, and we are proposing a kind of object-oriented Petri nets, called multi agent nets (MANs). In this letter, we consider the reachability analysis of MANs. We propose an algorithm for generating an abstract state space of a multi agent net, and report results of computational experiments.

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.

Petri nets are a well-known graphical and modeling tool for concurrent and distributed systems, and there have been many results on the theory, and also on practical applications. In the last decade, various Object-Oriented Petri nets (OO-nets) are proposed. As object orientation was adopted for programming languages, extension to OO-nets inspired from object-oriented programming is a natural flow. This article presents state-of-the-art on OO-nets.

A cloud system is defined as a large scale computer system that contains running high performance computers and responds to a large number of incoming tasks over the Internet. In this paper, we consider the problem to schedule computational jobs efficiently regarding system resource constraint and introduce a cuckoo search (CS) algorithm. Experimental results show that CS outperforms the genetic algorithm in terms of fitness value.

In automated transport applications, the design of a task allocation policy becomes a complex problem when there are several agents in the system and conflicts between them may arise, affecting the system's performance. In this situation, to achieve a globally optimal result would require the complete knowledge of the system's model, which is infeasible for real systems with huge state spaces and unknown state-transition probabilities. Reinforcement Learning (RL) methods have done well approximating optimal results in the processing of tasks, without requiring previous knowledge of the system's model. However, to our knowledge, there are not many RL methods focused on the task allocation problem in transportation systems, and even fewer directly used to allocate tasks, considering the risk of conflicts between agents. In this paper, we propose an option-based RL algorithm with conditioned updating to make agents learn a task allocation policy to complete tasks while preventing conflicts between them. We use a multicar elevator (MCE) system as test application. Simulation results show that with our algorithm, elevator cars in the same shaft effectively learn to respond to service calls without interfering with each other, under different passenger arrival rates, and system configurations.

Signal Transition Graphs (STG'S) [1] are Petrinets [2], which were introduced to represent a behavior of asynchronous circuits. To derive logic functions from an STG, the reachability graph should be constructed. In the verification of STG's some method based on Occurrence nets (OCN) and its prefix, called unfollding, has been proposed [3], [4]. OCN's can represent both causality and concurrency between two nodes by net stryctyre. In this paper, we propose an efficient algorithm to derive a logic function by generating sub-state space of a given STG using the structural properties of OCN. The proposed algorithm can be seem as a parallel algorithm for deriving a logic function.

A service-oriented architecture builds the entire system using a combination of independent software components. Such an architecture can be applied to a wide variety of computer systems. The problem of synthesizing service implementation models from choreography representing the overall specifications of service interaction is known as the choreography realization problem. In automatic synthesis, software models should be simple enough to be easily understood by software engineers. In this paper, we discuss a semi-formal method for synthesizing hierarchical state machine models for the choreography realization problem. The proposed method is evaluated using metrics for intelligibility.