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Daniel E. Neiman

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3 papers

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ICAPS Conference 1996 Conference Paper

A Cooperative Repair Method for a Distributed Scheduling System

Daniel E. Neiman
Victor R. Lesser

For some time, we have been studying the issues involved in job-shop scheduling in an environment of cooperative distributed agents, none of which has a complete view of the resources available, or of the tasks to be scheduled. Schedules produced cooperatively by such distributed agents using constraint satisfaction methods are often not optimal because of the inherent asynchronicity of the distributed scheduling process, the bounded rationality of the scheduling agents, and the difficulty in completely integrating meta-level heuristics into an agent’s local scheduling processes. This paper describes a modification to distributed scheduling in which the loosely coupled distributed processing methods are supplemented with a tightly coupled parallel repair process. We explore the implications on the repair process of a distributed environment in which the designer of the repair algorithm must address issues of agent communication and organization. We describe a search algorithm and a set of heuristics for guiding the repair process and present some experimental results in the context of the Distributed ARM, an airline resource scheduling system.

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AAAI Conference 1994 Conference Paper

Exploiting Meta-Level Information in a Distributed Scheduling System

Daniel E. Neiman
Victor R. Lesser

In this paper, we study the problem of achieving efficient interaction in a distributed scheduling system whose scheduling agents may borrow resources from one another. Specifically, we expand on Sycara’ s use of resource texture measures in a distributed scheduling system with a central resource monitor for each resource type and apply it to the decentralized case. We show how analysis of the abstracted resource requirements of remote agents can guide an agent’ s choice of local scheduling activities not only in determining local constraint tightness, but also in identifying activities that reduce global uncertainty. We also exploit meta-level information to allow the scheduling agents to make reasoned decisions about when to attempt to solve impasses locally through backtracking and constraint relaxation and when to request resources from remote agents. Finally, we describe the current state of negotiation in our system and discuss plans for integrating a more sophisticated cost model into the negotiation protocol. This work is presented in the context of the Distributed Airport Resource Management System, a multi-agent system for solving airport ground service scheduling problems.

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AAAI Conference 1991 Conference Paper

Control Issues in Parallel Rule-Firing Production Systems

Daniel E. Neiman

When rules are executed in a parallel production systern, the goal of control is to ensure both that a highquality solution is achieved and that processing resources are used effectively. We argue that the conventional conflict resolution algorithm is not suitable as a control mechanism for parallel rule-firing systems. The necessity for examining all eligible rules within a system imposes a synchronization delay which limits processor utilization. Rather than perform conflict resolution, we propose that rules should be executed asynchronously as soon as they become enabled, however, this approach leaves the problem of controlling the computation unsolved. We have identified three distinct types of control, program sequencing, heuristic control, and dynamic scheduling, which are required for efficient and correct parallel execution of rules. We discuss the issues involved in implementing each type of control without undue overhead within the context of our system, a parallel rule-firing system with an augmented agenda manager.

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