IMPLEMENTING DISTRIBUTED AI SYSTEMS USING MACE.

Les Gasser, Carl Braganza, Nava Herman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The authors describe the experimental distributed artificial intelligence (DAI) development system MACE (Multi-Agent Computing Environment) using the implementation of a distributed blackboard system as an example. MACE is an instrumented testbed for building DAI systems at different levels of granularity. MACE agents run in parallel, and communicate via messages. They have facilities for knowledge representation (e. g. , models of other agents) and reasoning. The MACE environment maps agents to processors, handles interagent communication, and provides a language for describing agents, tracing and instrumentation, a facility for remote demons, and a collection of system-agents that construct user-agents from descriptions, monitor execution, handle errors, and interface to a user. MACE is implemented on a 16-node Intel SYM-1 large-memory hypercube and in a Lisp machine environment. MACE has been used to model lower-level parallelism (several distributed production rule systems) and to build higher-level distributed problem-solving architectures (distributed blackboard and contract-net schemes).

Original languageEnglish (US)
Title of host publicationUnknown Host Publication Title
PublisherIEEE
Pages315-320
Number of pages6
ISBN (Print)0818607637
StatePublished - 1987
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)

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