Showing papers on "Contract Net Protocol published in 1995"

AgenTalk: describing multiagent coordination protocols with inheritance

Abstract: Presents the basic concepts behind AgenTalk, a language used for describing coordination protocols in multiagent systems. Many coordination protocols, such as the contract net protocol, have been proposed, and many application-specific coordination protocols are expected to be required as soon as the building of more software agents begins. Thus, a language for defining and implementing such coordination protocols plays a crucial role in the development of multiagent systems. By incorporating an inheritance mechanism, AgenTalk allows coordination protocols to be incrementally defined and easily customized to suit various application domains. Its capability is demonstrated by describing the contract net and multistage negotiation protocols in AgenTalk using its inheritance mechanism.

AgenTalk: Coordination Protocol Description for Multiagent Systems.

Abstract: In multiagent systems, achieving coordination among autonomous agents is a major problem. Generally, a high-level protocol needs to be designed to achieve effective coordination. In the field of distributed artificial intelligence, protocols for achieving coordination have been proposed, such as the contract net protocol for task allocation (Smith 1980), and the multistage negotiation protocol for resource allocation under global constraints (Conry et al. 1991). These protocols have been further customized to suit various application domains. In addition, as software agents proliferate, demand for customized protocols will increase. In order to facilitate the development of multiagent coordination protocols, we designed a new language called AgenTalk. AgenTalk is not meant to be a forreal specification language; rather it is meant to be a programming language capable of implementing protocols and agents behaving according to the protocols. Its design policies are as follows. Explicit state representation of a protocol: An extended finite state machine which allows variables is used as a basis to describe coordination protocols. We call the representation of this state machine a script. Using this model, states of a protocol are explicitly defined, and actions of an agent can easily be defined for each state. Agent Program Application-specific Scdpts II l

Synthesis of protocol entities specifications from service specifications in a Petri net model with registers

Abstract: In general, the services of a distributed system are provided by some cooperative protocol entities. The protocol entities must exchange some data values and synchronization messages in order to ensure the temporal ordering of the events which are described in a service specification of the distributed system. It is desirable that a correct protocol entity specification for each node can be derived automatically from a given service specification. In this paper, we propose an algorithm which synthesizes a correct protocol entity specification automatically from a service specification in a Petri Net model with Registers called PNR model. In our model, parallel events and selective operations can be described naturally. The control flow of a service specification must be described as a free-choice net in order to simplify the derivation algorithm, however, many practical systems can be described in this class. In our approach, since each protocol entity specification is also described in our PNR model, we can easily understand what events can be executed in parallel at each protocol entity.

Learning to Reduce Communication Cost on Task Negotiation among Multiple Autonomous Mobile Robots

Abstract: This paper describes Lemming, a learning system for task negotiation in multi-robot environments. Lemming focuses on the problem of communication costs on Contract Net Protocol. Contract Net Protocol has been recognized as an attractive way for task negotiation. However, it is difficult for multi-robot systems to use wide-band communication lines enough to utilize standard Contract Net Protocol. It has been observed that the main communication cost on Contract Net Protocol is caused by broadcasting task announcements. In order to reduce this cost Lemming uses Case-Based Reasoning(CBR). By using CBR, Lemming can derive useful knowledge from messages in Contract Net Protocol and can find a suitable robot that should receive task announcements. We evaluate the idea of Lemming in a simulated multirobot environment. The result shows the advantage of Lemming over standard contract net systems.

Information processing system for an architecture model capable of interfacing with humans and capable of being modified

Abstract: In an information processing system for architecture model, which comprises a plurality of software modules divided into independent element functions and a work memory area for reading and writing various information as a shared medium, there are provided a work memory area management module 106 for managing history of task phase descriptions delivered to the work memory area as context information, a bid arbiter module 107 for evaluating bids in contract net protocol using the accumulated context information, and a dialog manager module 105 for explaining course of context dependent processing to the user and for providing means to customize the context dependent processing to the user, whereby the software module groups give and take task phase descriptions via the work memory area using the work memory area access procedure, and the bid arbiter module 107 evaluates bids based on the context managed by the work memory area management module 106 so that module groups are operated according to mutual context.

Evaluating a contract net-based heterarchical scheduling approach for flexible manufacturing

Abstract: This paper discusses a heterarchical scheduling approach for flexible manufacturing systems. The workcells comprising the manufacturing process and the products to be generated are modeled as autonomous agents which interact dynamically to generate the production schedule for each product unit. The interaction scheme combines production reservation with a bidding mechanism using the contract net protocol. The effectiveness of this approach is demonstrated using simulation experiments that compare its performance to heuristic dispatching rules commonly used in industry.

Task negotiation for distributed manufacturing systems

Abstract: This paper deals with a new architecture and negotiation protocol for the dynamic scheduling of manufacturing systems. The architecture is based on the paradigm of distributed intelligence and multi-agent systems. What concerns the architecture is the existence of agents representing the tasks together with agents representing the resources. The well known contract net protocol has been adapted to handle the temporal constraints, namely the deadline submission. The purpose of this protocol is to dynamically assign operations to the resources of the manufacturing system in order to accomplish the proposed tasks. This protocol involves a renegotiation phase whenever exceptions appear. It also deals with conflict situations, namely with the case of the "indecision problem". The approach proposed assume that deadlines are the most important constraints to consider, thus the acceptance or refuse of a resource for a specific operation depends on the capability of executing the operation in the specified deadline.

A Quantitative Analysis of the Contract Net Protocol

Abstract: The Contract Net Protocol (CNP) [Smith, 1980] assigns a subtask to agents which are involved in multiagent problem solving. Although the logical aspects of the negotiation protocol have been analyzed, the properties of protocol dynamics remain unclear. This paper introduces our quantitative analysis of protocol dynamics which is essential for constructing continuous reaitime applications. We carried out a simulation which based on queueing theory to practice the purpose described above. Two kinds of agent, manager and contractor, exist within the simulation. Managers provide tasks to contractors which undertake them as follows: first, when a task arrives, the manager responsible for it announces it with a bidding deadline to all of contractors immediately; second, each contractor selects from all the announced tasks, the one that best matches its own standards, and bids for it; finally, the manager chooses the most appropriate bid, and awards it to that agent; a manager can make multiple announcements simultaneously while a contractor can bid for only one task at a time. Each manager and contractor has a evaluation function fi and gj, respectively. Manager i awards a bidder that achieves maxj []i(j)] and contractor j selects task that achieves max~Lqj(i)]. The .?i and gj is generated as a list containing the natural numbers from I to 100. The service time for a task and the bidding period is fixed at 1 and 0.1 respectively. We say managers or contractors are homogeneous when fix(J) = fib(J) gj, (i) = gj2(i), otherwise heterogeneous. The manager utility and the contractor utility is respectively calculated by _.L~, ~"~--’l ~"~-~=l/~(J), wherein c is the number